Bonus-Assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bonus Assignment 1\n",
    "\n",
    "This is a Bonus Assignment try to complete all other Assignments before you reach here \n",
    "\n",
    "Try First Attempting Question 2 and then Question 1 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 1\n",
    "Solve this question on Kaggle! \n",
    "Download the notebook and submit it separately along with the other questions.\n",
    "\n",
    "https://www.kaggle.com/competitions/house-prices-advanced-regression-techniques/overview\n",
    "\n",
    "Use everything that you have learnt so far.\n",
    "\n",
    "Analyse the data. Drop, scale or normalize features. Merge features if they correlated to make some meaningful features. \n",
    "\n",
    "Try out all the regression models. Use cross validation to find best parameters for each model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 2 : Regression using SVM and Tree Algorithms\n",
    "\n",
    "In this question, we will be using the **insurance.csv** file which contain information on insurance charges based on the following informations: age,sex,bmi,region,number of children and whether the person is a smoker or not. You need to predict the charges based on the information given.\n",
    "\n",
    "### 1. Load the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(os.path.expanduser('~/Documents/projects/ML-fundamentals/Week 1/Bonus Assignment'))\n",
    "insurance = pd.read_csv('insurance.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age     sex     bmi  children smoker     region      charges\n",
       "0   19  female  27.900         0    yes  southwest  16884.92400\n",
       "1   18    male  33.770         1     no  southeast   1725.55230\n",
       "2   28    male  33.000         3     no  southeast   4449.46200\n",
       "3   33    male  22.705         0     no  northwest  21984.47061\n",
       "4   32    male  28.880         0     no  northwest   3866.85520"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Separate the numerical and categorical columns.\n",
    "### 3. Label Encode the categorical columns.\n",
    "### 4. Scale the numerical columns. (Scale the charges separately so that you can calculate errors afterwards.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder, MinMaxScaler\n",
    "categorical_features = ['sex', 'smoker', 'region']\n",
    "lbl = LabelEncoder()\n",
    "for feature in categorical_features:\n",
    "    insurance[feature] = lbl.fit_transform(insurance[feature])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex     bmi  children  smoker  region      charges\n",
       "0   19    0  27.900         0       1       3  16884.92400\n",
       "1   18    1  33.770         1       0       2   1725.55230\n",
       "2   28    1  33.000         3       0       2   4449.46200\n",
       "3   33    1  22.705         0       0       1  21984.47061\n",
       "4   32    1  28.880         0       0       1   3866.85520"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 2, 1, 0])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance.region.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array(insurance.drop(columns=['charges'], axis=1))\n",
    "y = np.array(insurance.charges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "scalerx = MinMaxScaler()\n",
    "scalery = MinMaxScaler()\n",
    "X = scalerx.fit_transform(X)\n",
    "y = scalery.fit_transform(y.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.25161076, 0.00963595, 0.05311516, ..., 0.00810808, 0.01414352,\n",
       "       0.44724873])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = y.reshape(1, -1)[0]\n",
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Split the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "Xtrain, Xtest, ytrain, ytest = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Support Vector Regressor\n",
    "\n",
    "Here , you will use the SVR model from sklearn.svm and fit it on the training data. Then predict on the test data and calaculate MAE, MSE. But...\n",
    "\n",
    "The SVR class contains many hyperparameters, example : kernel can have the following values : linear, rbf, poly, sigmoid.\n",
    "\n",
    "Use **RandomizedSearchCV** from sklearn.model_selection , create a dictionary with keys 'kernel' and 'gamma' . As values of the keys, create a list of some possible values. Run a 3-fold cross validation test (cv=3) and find the best parameters. Then initiate the SVR model with those parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVR\n",
    "from sklearn.model_selection import RandomizedSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "hyp_para_dist = {\n",
    "    'C' : range(1, 11),\n",
    "    'kernel' : ['rbf', 'poly', 'linear', 'sigmoid'],\n",
    "    'degree' : range(1, 5),\n",
    "    'gamma' : np.linspace(0, 1, 10)\n",
    "}\n",
    "svr = SVR()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "random_search = RandomizedSearchCV(estimator=svr, param_distributions=hyp_para_dist, random_state=42, scoring='accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:993: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 982, in _score\n",
      "    scores = scorer(estimator, X_test, y_test, **score_params)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 253, in __call__\n",
      "    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_scorer.py\", line 350, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **scoring_kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 213, in wrapper\n",
      "    return func(*args, **kwargs)\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 213, in accuracy_score\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_classification.py\", line 105, in _check_targets\n",
      "    raise ValueError(\"{0} is not supported\".format(y_type))\n",
      "ValueError: continuous is not supported\n",
      "\n",
      "  warnings.warn(\n",
      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/model_selection/_search.py:1051: UserWarning: One or more of the test scores are non-finite: [nan nan nan nan nan nan nan nan nan nan]\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(estimator=SVR(),\n",
       "                   param_distributions={&#x27;C&#x27;: range(1, 11),\n",
       "                                        &#x27;degree&#x27;: range(1, 5),\n",
       "                                        &#x27;gamma&#x27;: array([0.        , 0.11111111, 0.22222222, 0.33333333, 0.44444444,\n",
       "       0.55555556, 0.66666667, 0.77777778, 0.88888889, 1.        ]),\n",
       "                                        &#x27;kernel&#x27;: [&#x27;rbf&#x27;, &#x27;poly&#x27;, &#x27;linear&#x27;,\n",
       "                                                   &#x27;sigmoid&#x27;]},\n",
       "                   random_state=42, scoring=&#x27;accuracy&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomizedSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.model_selection.RandomizedSearchCV.html\">?<span>Documentation for RandomizedSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomizedSearchCV(estimator=SVR(),\n",
       "                   param_distributions={&#x27;C&#x27;: range(1, 11),\n",
       "                                        &#x27;degree&#x27;: range(1, 5),\n",
       "                                        &#x27;gamma&#x27;: array([0.        , 0.11111111, 0.22222222, 0.33333333, 0.44444444,\n",
       "       0.55555556, 0.66666667, 0.77777778, 0.88888889, 1.        ]),\n",
       "                                        &#x27;kernel&#x27;: [&#x27;rbf&#x27;, &#x27;poly&#x27;, &#x27;linear&#x27;,\n",
       "                                                   &#x27;sigmoid&#x27;]},\n",
       "                   random_state=42, scoring=&#x27;accuracy&#x27;)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: SVR</label><div class=\"sk-toggleable__content fitted\"><pre>SVR()</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SVR<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVR.html\">?<span>Documentation for SVR</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SVR()</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(estimator=SVR(),\n",
       "                   param_distributions={'C': range(1, 11),\n",
       "                                        'degree': range(1, 5),\n",
       "                                        'gamma': array([0.        , 0.11111111, 0.22222222, 0.33333333, 0.44444444,\n",
       "       0.55555556, 0.66666667, 0.77777778, 0.88888889, 1.        ]),\n",
       "                                        'kernel': ['rbf', 'poly', 'linear',\n",
       "                                                   'sigmoid']},\n",
       "                   random_state=42, scoring='accuracy')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_search.fit(Xtrain, ytrain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Parameters: {'kernel': 'linear', 'gamma': 0.1111111111111111, 'degree': 1, 'C': 8}\n"
     ]
    }
   ],
   "source": [
    "print(\"Best Parameters:\", random_search.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "Svr = SVR(kernel='linear', gamma=0.1, degree=1, C=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVR(C=8, degree=1, gamma=0.1, kernel=&#x27;linear&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" checked><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;SVR<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVR.html\">?<span>Documentation for SVR</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVR(C=8, degree=1, gamma=0.1, kernel=&#x27;linear&#x27;)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "SVR(C=8, degree=1, gamma=0.1, kernel='linear')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Svr.fit(Xtrain, ytrain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "ypred = Svr.predict(Xtest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.009377275308037112"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "mean_squared_error(ytest, ypred)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}