learn_pytorch_27_pytorch实战项目之多元线性回归房价预测1调试版.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 房价数据集介绍：源自kaggle竞赛 \n",
    "kaggle官网：https://www.kaggle.com/   \n",
    "数据集官网：https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data?select=train.csv   \n",
    "参考：动手学深度学习pytorch版https://github.com/ShusenTang/Dive-into-DL-PyTorch  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 实战开始"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1 导入需要的模块、包等\n",
    "import torch\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import torch.nn as nn\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 81)\n",
      "(1459, 80)\n"
     ]
    }
   ],
   "source": [
    "# 2 数据处理\n",
    "# 2.1 载入数据、查看数据信息\n",
    "\n",
    "train_data = pd.read_csv(\"./kg_train.csv\")\n",
    "test_data = pd.read_csv(\"./kg_test.csv\")\n",
    "\n",
    "print(train_data.shape)\n",
    "print(test_data.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities  ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold  \\\n",
       "0         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "1         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      5   \n",
       "2         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      9   \n",
       "3         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "4         Lvl    AllPub  ...        0    NaN   NaN         NaN       0     12   \n",
       "\n",
       "  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0   2008        WD         Normal     208500  \n",
       "1   2007        WD         Normal     181500  \n",
       "2   2008        WD         Normal     223500  \n",
       "3   2006        WD        Abnorml     140000  \n",
       "4   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.2 先去掉ID列，再将训练集和测试集的79个特征按行连接 \n",
    "all_features = pd.concat((train_data.iloc[:, 1:-1], test_data.iloc[:, 1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2919, 79)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities LotConfig  ... ScreenPorch PoolArea PoolQC Fence  \\\n",
       "0         Lvl    AllPub    Inside  ...           0        0    NaN   NaN   \n",
       "1         Lvl    AllPub       FR2  ...           0        0    NaN   NaN   \n",
       "2         Lvl    AllPub    Inside  ...           0        0    NaN   NaN   \n",
       "3         Lvl    AllPub    Corner  ...           0        0    NaN   NaN   \n",
       "4         Lvl    AllPub       FR2  ...           0        0    NaN   NaN   \n",
       "\n",
       "  MiscFeature MiscVal  MoSold  YrSold  SaleType  SaleCondition  \n",
       "0         NaN       0       2    2008        WD         Normal  \n",
       "1         NaN       0       5    2007        WD         Normal  \n",
       "2         NaN       0       9    2008        WD         Normal  \n",
       "3         NaN       0       2    2006        WD        Abnorml  \n",
       "4         NaN       0      12    2008        WD         Normal  \n",
       "\n",
       "[5 rows x 79 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.3 数据预处理:数值特征标准化处理，缺失值用0填充\n",
    "numeric_features = all_features.dtypes[all_features.dtypes != 'object'].index\n",
    "all_features[numeric_features] = all_features[numeric_features].apply(lambda x: (x - x.mean()) / (x.std()))\n",
    "all_features = all_features.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.184443</td>\n",
       "      <td>-0.217841</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.551918</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.458096</td>\n",
       "      <td>-0.072032</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.055935</td>\n",
       "      <td>0.137173</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.302516</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.398622</td>\n",
       "      <td>-0.078371</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.551918</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.629439</td>\n",
       "      <td>0.518814</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>2.131647</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.167877</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.672275</td>\n",
       "      <td>0.500430</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>Shed</td>\n",
       "      <td>1.144116</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>0.918095</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.243916</td>\n",
       "      <td>-0.010665</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>0.658221</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.027119</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Shed</td>\n",
       "      <td>0.527270</td>\n",
       "      <td>1.763290</td>\n",
       "      <td>0.918095</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.167877</td>\n",
       "      <td>RM</td>\n",
       "      <td>-0.784145</td>\n",
       "      <td>-0.513264</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.815205</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.124875</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.826981</td>\n",
       "      <td>-0.348436</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.920274</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.029737</td>\n",
       "      <td>0.130834</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.551918</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.672275</td>\n",
       "      <td>0.222630</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>0.289865</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.355000</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR2</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>2.846658</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.929291</td>\n",
       "      <td>0.061352</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>0.658221</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.095332</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>GdWo</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.285475</td>\n",
       "      <td>RM</td>\n",
       "      <td>-0.784145</td>\n",
       "      <td>-0.513264</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>GdPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>0.289865</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.136032</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>CulDSac</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Shed</td>\n",
       "      <td>1.144116</td>\n",
       "      <td>-1.183561</td>\n",
       "      <td>1.678572</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.772910</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.115409</td>\n",
       "      <td>0.078976</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Shed</td>\n",
       "      <td>0.791633</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.141607</td>\n",
       "      <td>0.447177</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.078492</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.029737</td>\n",
       "      <td>-0.330685</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>0.918095</td>\n",
       "      <td>COD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>1.357650</td>\n",
       "      <td>0.513109</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.763290</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.285475</td>\n",
       "      <td>RM</td>\n",
       "      <td>-0.527130</td>\n",
       "      <td>-0.344759</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Grvl</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Bnk</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>GdPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.078492</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.243916</td>\n",
       "      <td>-0.054027</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.478499</td>\n",
       "      <td>RM</td>\n",
       "      <td>-1.083997</td>\n",
       "      <td>-0.753660</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.078492</td>\n",
       "      <td>-0.602858</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.243707</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>1.678572</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>1.743173</td>\n",
       "      <td>0.515010</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>0.289865</td>\n",
       "      <td>0.918095</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.398622</td>\n",
       "      <td>-0.376330</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>1.678572</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>1.229142</td>\n",
       "      <td>0.166082</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>1.678572</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.955489</td>\n",
       "      <td>0.780130</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>CulDSac</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>2.131647</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-0.638270</td>\n",
       "      <td>RM</td>\n",
       "      <td>-0.398622</td>\n",
       "      <td>-0.487399</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>0.157619</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1429</th>\n",
       "      <td>-0.638270</td>\n",
       "      <td>RM</td>\n",
       "      <td>-0.826981</td>\n",
       "      <td>-0.397885</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.183561</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1430</th>\n",
       "      <td>-0.167877</td>\n",
       "      <td>RM</td>\n",
       "      <td>0.243916</td>\n",
       "      <td>-0.140499</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.815205</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1431</th>\n",
       "      <td>-0.638270</td>\n",
       "      <td>C (all)</td>\n",
       "      <td>-0.013099</td>\n",
       "      <td>0.278672</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1432</th>\n",
       "      <td>3.124875</td>\n",
       "      <td>C (all)</td>\n",
       "      <td>-0.826981</td>\n",
       "      <td>-0.148106</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1433</th>\n",
       "      <td>-0.167877</td>\n",
       "      <td>C (all)</td>\n",
       "      <td>-0.398622</td>\n",
       "      <td>-0.208966</td>\n",
       "      <td>Grvl</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Bnk</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.815205</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1434</th>\n",
       "      <td>1.478499</td>\n",
       "      <td>RM</td>\n",
       "      <td>-1.212504</td>\n",
       "      <td>-0.560431</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>HLS</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>2.437291</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.551918</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1435</th>\n",
       "      <td>1.478499</td>\n",
       "      <td>RM</td>\n",
       "      <td>-1.083997</td>\n",
       "      <td>-0.802094</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>HLS</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>2.472888</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>2.131647</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1436</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.013099</td>\n",
       "      <td>1.700506</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1437</th>\n",
       "      <td>0.772910</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.184443</td>\n",
       "      <td>-0.226083</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1438</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.029737</td>\n",
       "      <td>-0.133399</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1439</th>\n",
       "      <td>0.537713</td>\n",
       "      <td>RL</td>\n",
       "      <td>3.028250</td>\n",
       "      <td>0.115619</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.063257</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Low</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>2.170313</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.183561</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Alloca</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1441</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.262472</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>1.100634</td>\n",
       "      <td>0.437414</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.763290</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.800783</td>\n",
       "      <td>0.178634</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>New</td>\n",
       "      <td>Partial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1444</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>0</td>\n",
       "      <td>2.385711</td>\n",
       "      <td>2.672993</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1445</th>\n",
       "      <td>0.772910</td>\n",
       "      <td>RM</td>\n",
       "      <td>0.372424</td>\n",
       "      <td>-0.399152</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.763290</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1446</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-1.212504</td>\n",
       "      <td>-0.951327</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1447</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.484294</td>\n",
       "      <td>0.000493</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.394934</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1448</th>\n",
       "      <td>0.772910</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.211473</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-1.183561</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1449</th>\n",
       "      <td>2.889679</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.102842</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.815205</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.101067</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1451</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.458096</td>\n",
       "      <td>0.407745</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.446848</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.094855</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>2.131647</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.095742</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>GdPrv</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.078492</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.043758</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.078492</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>2.419286</td>\n",
       "      <td>RM</td>\n",
       "      <td>-2.069222</td>\n",
       "      <td>-1.049083</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>-0.815205</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>-0.873466</td>\n",
       "      <td>RL</td>\n",
       "      <td>3.884968</td>\n",
       "      <td>1.246594</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.026577</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1457</th>\n",
       "      <td>0.655311</td>\n",
       "      <td>RL</td>\n",
       "      <td>-0.312950</td>\n",
       "      <td>0.034599</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>Shed</td>\n",
       "      <td>1.144116</td>\n",
       "      <td>0.289865</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>0.067320</td>\n",
       "      <td>RL</td>\n",
       "      <td>0.201080</td>\n",
       "      <td>-0.068608</td>\n",
       "      <td>Pave</td>\n",
       "      <td>0</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.285886</td>\n",
       "      <td>-0.063139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.089577</td>\n",
       "      <td>1.763290</td>\n",
       "      <td>-1.363335</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2919 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      MSSubClass MSZoning  LotFrontage   LotArea Street Alley LotShape  \\\n",
       "0       0.067320       RL    -0.184443 -0.217841   Pave     0      Reg   \n",
       "1      -0.873466       RL     0.458096 -0.072032   Pave     0      Reg   \n",
       "2       0.067320       RL    -0.055935  0.137173   Pave     0      IR1   \n",
       "3       0.302516       RL    -0.398622 -0.078371   Pave     0      IR1   \n",
       "4       0.067320       RL     0.629439  0.518814   Pave     0      IR1   \n",
       "5      -0.167877       RL     0.672275  0.500430   Pave     0      IR1   \n",
       "6      -0.873466       RL     0.243916 -0.010665   Pave     0      Reg   \n",
       "7       0.067320       RL     0.000000  0.027119   Pave     0      IR1   \n",
       "8      -0.167877       RM    -0.784145 -0.513264   Pave     0      Reg   \n",
       "9       3.124875       RL    -0.826981 -0.348436   Pave     0      Reg   \n",
       "10     -0.873466       RL     0.029737  0.130834   Pave     0      Reg   \n",
       "11      0.067320       RL     0.672275  0.222630   Pave     0      IR1   \n",
       "12     -0.873466       RL     0.000000  0.355000   Pave     0      IR2   \n",
       "13     -0.873466       RL     0.929291  0.061352   Pave     0      IR1   \n",
       "14     -0.873466       RL     0.000000  0.095332   Pave     0      IR1   \n",
       "15     -0.285475       RM    -0.784145 -0.513264   Pave     0      Reg   \n",
       "16     -0.873466       RL     0.000000  0.136032   Pave     0      IR1   \n",
       "17      0.772910       RL     0.115409  0.078976   Pave     0      Reg   \n",
       "18     -0.873466       RL    -0.141607  0.447177   Pave     0      Reg   \n",
       "19     -0.873466       RL     0.029737 -0.330685   Pave     0      Reg   \n",
       "20      0.067320       RL     1.357650  0.513109   Pave     0      IR1   \n",
       "21     -0.285475       RM    -0.527130 -0.344759   Pave  Grvl      Reg   \n",
       "22     -0.873466       RL     0.243916 -0.054027   Pave     0      Reg   \n",
       "23      1.478499       RM    -1.083997 -0.753660   Pave     0      Reg   \n",
       "24     -0.873466       RL     0.000000 -0.243707   Pave     0      IR1   \n",
       "25     -0.873466       RL     1.743173  0.515010   Pave     0      Reg   \n",
       "26     -0.873466       RL    -0.398622 -0.376330   Pave     0      Reg   \n",
       "27     -0.873466       RL     1.229142  0.166082   Pave     0      Reg   \n",
       "28     -0.873466       RL    -0.955489  0.780130   Pave     0      IR1   \n",
       "29     -0.638270       RM    -0.398622 -0.487399   Pave     0      IR1   \n",
       "...          ...      ...          ...       ...    ...   ...      ...   \n",
       "1429   -0.638270       RM    -0.826981 -0.397885   Pave     0      Reg   \n",
       "1430   -0.167877       RM     0.243916 -0.140499   Pave     0      Reg   \n",
       "1431   -0.638270  C (all)    -0.013099  0.278672   Pave     0      Reg   \n",
       "1432    3.124875  C (all)    -0.826981 -0.148106   Pave     0      Reg   \n",
       "1433   -0.167877  C (all)    -0.398622 -0.208966   Grvl     0      Reg   \n",
       "1434    1.478499       RM    -1.212504 -0.560431   Pave     0      IR1   \n",
       "1435    1.478499       RM    -1.083997 -0.802094   Pave     0      IR1   \n",
       "1436   -0.873466       RL    -0.013099  1.700506   Pave     0      IR1   \n",
       "1437    0.772910       RL    -0.184443 -0.226083   Pave     0      Reg   \n",
       "1438   -0.873466       RL     0.029737 -0.133399   Pave     0      Reg   \n",
       "1439    0.537713       RL     3.028250  0.115619   Pave     0      Reg   \n",
       "1440   -0.873466       RL     0.000000  5.063257   Pave     0      IR1   \n",
       "1441   -0.873466       RL     0.000000 -0.262472   Pave     0      IR1   \n",
       "1442   -0.873466       RL     1.100634  0.437414   Pave     0      Reg   \n",
       "1443   -0.873466       RL     0.800783  0.178634   Pave     0      Reg   \n",
       "1444   -0.873466        0     2.385711  2.672993   Pave     0      Reg   \n",
       "1445    0.772910       RM     0.372424 -0.399152   Pave     0      Reg   \n",
       "1446    2.419286       RM    -1.212504 -0.951327   Pave     0      Reg   \n",
       "1447   -0.873466       RL    -0.484294  0.000493   Pave     0      IR1   \n",
       "1448    0.772910       RL     0.000000  0.211473   Pave     0      IR1   \n",
       "1449    2.889679       RM    -2.069222 -1.102842   Pave     0      Reg   \n",
       "1450    2.419286       RM    -2.069222 -1.101067   Pave     0      Reg   \n",
       "1451   -0.873466       RL     0.458096  0.407745   Pave     0      Reg   \n",
       "1452    2.419286       RM    -2.069222 -1.094855   Pave     0      Reg   \n",
       "1453    2.419286       RM    -2.069222 -1.095742   Pave     0      Reg   \n",
       "1454    2.419286       RM    -2.069222 -1.043758   Pave     0      Reg   \n",
       "1455    2.419286       RM    -2.069222 -1.049083   Pave     0      Reg   \n",
       "1456   -0.873466       RL     3.884968  1.246594   Pave     0      Reg   \n",
       "1457    0.655311       RL    -0.312950  0.034599   Pave     0      Reg   \n",
       "1458    0.067320       RL     0.201080 -0.068608   Pave     0      Reg   \n",
       "\n",
       "     LandContour Utilities LotConfig  ... ScreenPorch  PoolArea PoolQC  Fence  \\\n",
       "0            Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1            Lvl    AllPub       FR2  ...   -0.285886 -0.063139      0      0   \n",
       "2            Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "3            Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "4            Lvl    AllPub       FR2  ...   -0.285886 -0.063139      0      0   \n",
       "5            Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  MnPrv   \n",
       "6            Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "7            Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "8            Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "9            Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "10           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "11           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "12           Lvl    AllPub    Inside  ...    2.846658 -0.063139      0      0   \n",
       "13           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "14           Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0   GdWo   \n",
       "15           Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0  GdPrv   \n",
       "16           Lvl    AllPub   CulDSac  ...   -0.285886 -0.063139      0      0   \n",
       "17           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "18           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "19           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  MnPrv   \n",
       "20           Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "21           Bnk    AllPub    Inside  ...   -0.285886 -0.063139      0  GdPrv   \n",
       "22           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "23           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "24           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  MnPrv   \n",
       "25           Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "26           Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "27           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "28           Lvl    AllPub   CulDSac  ...   -0.285886 -0.063139      0      0   \n",
       "29           Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "...          ...       ...       ...  ...         ...       ...    ...    ...   \n",
       "1429         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  MnPrv   \n",
       "1430         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1431         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1432         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1433         Bnk    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1434         HLS    AllPub    Inside  ...    2.437291 -0.063139      0      0   \n",
       "1435         HLS    AllPub    Inside  ...    2.472888 -0.063139      0      0   \n",
       "1436         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1437         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1438         Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "1439         Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "1440         Low    AllPub    Inside  ...    2.170313 -0.063139      0      0   \n",
       "1441         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1442         Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "1443         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1444         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1445         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1446         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1447         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1448         Lvl    AllPub    Corner  ...   -0.285886 -0.063139      0      0   \n",
       "1449         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1450         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1451         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1452         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1453         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  GdPrv   \n",
       "1454         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1455         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1456         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "1457         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0  MnPrv   \n",
       "1458         Lvl    AllPub    Inside  ...   -0.285886 -0.063139      0      0   \n",
       "\n",
       "     MiscFeature   MiscVal    MoSold    YrSold  SaleType  SaleCondition  \n",
       "0              0 -0.089577 -1.551918  0.157619        WD         Normal  \n",
       "1              0 -0.089577 -0.446848 -0.602858        WD         Normal  \n",
       "2              0 -0.089577  1.026577  0.157619        WD         Normal  \n",
       "3              0 -0.089577 -1.551918 -1.363335        WD        Abnorml  \n",
       "4              0 -0.089577  2.131647  0.157619        WD         Normal  \n",
       "5           Shed  1.144116  1.394934  0.918095        WD         Normal  \n",
       "6              0 -0.089577  0.658221 -0.602858        WD         Normal  \n",
       "7           Shed  0.527270  1.763290  0.918095        WD         Normal  \n",
       "8              0 -0.089577 -0.815205  0.157619        WD        Abnorml  \n",
       "9              0 -0.089577 -1.920274  0.157619        WD         Normal  \n",
       "10             0 -0.089577 -1.551918  0.157619        WD         Normal  \n",
       "11             0 -0.089577  0.289865 -1.363335       New        Partial  \n",
       "12             0 -0.089577  1.026577  0.157619        WD         Normal  \n",
       "13             0 -0.089577  0.658221 -0.602858       New        Partial  \n",
       "14             0 -0.089577 -0.446848  0.157619        WD         Normal  \n",
       "15             0 -0.089577  0.289865 -0.602858        WD         Normal  \n",
       "16          Shed  1.144116 -1.183561  1.678572        WD         Normal  \n",
       "17          Shed  0.791633  1.394934 -1.363335        WD         Normal  \n",
       "18             0 -0.089577 -0.078492  0.157619        WD         Normal  \n",
       "19             0 -0.089577 -0.446848  0.918095       COD        Abnorml  \n",
       "20             0 -0.089577  1.763290 -1.363335       New        Partial  \n",
       "21             0 -0.089577 -0.078492 -0.602858        WD         Normal  \n",
       "22             0 -0.089577  1.026577  0.157619        WD         Normal  \n",
       "23             0 -0.089577 -0.078492 -0.602858        WD         Normal  \n",
       "24             0 -0.089577 -0.446848  1.678572        WD         Normal  \n",
       "25             0 -0.089577  0.289865  0.918095        WD         Normal  \n",
       "26             0 -0.089577 -0.446848  1.678572        WD         Normal  \n",
       "27             0 -0.089577 -0.446848  1.678572        WD         Normal  \n",
       "28             0 -0.089577  2.131647 -1.363335        WD         Normal  \n",
       "29             0 -0.089577 -0.446848  0.157619        WD         Normal  \n",
       "...          ...       ...       ...       ...       ...            ...  \n",
       "1429           0 -0.089577 -1.183561 -1.363335        WD         Normal  \n",
       "1430           0 -0.089577 -0.815205 -1.363335        WD         Normal  \n",
       "1431           0 -0.089577  1.394934 -1.363335        WD        Abnorml  \n",
       "1432           0 -0.089577  1.394934 -1.363335        WD        Abnorml  \n",
       "1433           0 -0.089577 -0.815205 -1.363335        WD         Normal  \n",
       "1434           0 -0.089577 -1.551918 -1.363335       New        Partial  \n",
       "1435           0 -0.089577  2.131647 -1.363335        WD         Normal  \n",
       "1436           0 -0.089577  1.026577 -1.363335        WD         Normal  \n",
       "1437           0 -0.089577  1.394934 -1.363335        WD         Normal  \n",
       "1438           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1439           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1440           0 -0.089577 -1.183561 -1.363335        WD         Alloca  \n",
       "1441           0 -0.089577  1.394934 -1.363335        WD         Normal  \n",
       "1442           0 -0.089577  1.763290 -1.363335       New        Partial  \n",
       "1443           0 -0.089577  1.026577 -1.363335       New        Partial  \n",
       "1444           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1445           0 -0.089577  1.763290 -1.363335        WD         Normal  \n",
       "1446           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1447           0 -0.089577  1.394934 -1.363335        WD         Normal  \n",
       "1448           0 -0.089577 -1.183561 -1.363335        WD         Normal  \n",
       "1449           0 -0.089577 -0.815205 -1.363335        WD         Normal  \n",
       "1450           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1451           0 -0.089577 -0.446848 -1.363335        WD         Normal  \n",
       "1452           0 -0.089577  2.131647 -1.363335        WD        Abnorml  \n",
       "1453           0 -0.089577 -0.078492 -1.363335        WD         Normal  \n",
       "1454           0 -0.089577 -0.078492 -1.363335        WD         Normal  \n",
       "1455           0 -0.089577 -0.815205 -1.363335        WD        Abnorml  \n",
       "1456           0 -0.089577  1.026577 -1.363335        WD        Abnorml  \n",
       "1457        Shed  1.144116  0.289865 -1.363335        WD         Normal  \n",
       "1458           0 -0.089577  1.763290 -1.363335        WD         Normal  \n",
       "\n",
       "[2919 rows x 79 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2919, 79)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.4 数据预处理:非数值特征one-hot编码\n",
    "all_features = pd.get_dummies(all_features,dummy_na=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2919, 354)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_labels_mean = np.mean(train_data.SalePrice.values)\n",
    "train_labels_std = np.std(train_data.SalePrice.values)\n",
    "\n",
    "train_labels = (train_data.SalePrice.values - train_labels_mean) / train_labels_std\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.5 转为numpy的数据类型，再转为tensor\n",
    "n_train = train_data.shape[0]\n",
    "train_features = torch.tensor(all_features[:n_train].values, dtype=torch.float)\n",
    "train_labels = torch.tensor(train_labels, dtype=torch.float).unsqueeze(1)\n",
    "\n",
    "test_features = torch.tensor(all_features[n_train:].values, dtype=torch.float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3 创建模型\n",
    "class PolyLinearRegression(nn.Module):\n",
    "    def __init__(self, input_feature_numbers, out_labels_numbers):\n",
    "        super(PolyLinearRegression, self).__init__()\n",
    "        self.ploy = nn.Linear(input_feature_numbers, out_labels_numbers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = self.ploy(x)\n",
    "        return out\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 4 训练与测试\n",
    "def train_and_test():\n",
    "    if torch.cuda.is_available():\n",
    "        device = torch.device(\"cuda:0\")\n",
    "        model = PolyLinearRegression(train_features.shape[1], train_labels.shape[1])\n",
    "        model.to(device)\n",
    "    else:\n",
    "        device = torch.device(\"cpu\")\n",
    "        model = PolyLinearRegression(train_features.shape[1], train_labels.shape[1])\n",
    "        model.to(device)\n",
    "\n",
    "    criterion = nn.MSELoss()\n",
    "    optimizer = torch.optim.Adam(model.parameters(), lr=0.0001)\n",
    "\n",
    "    loss_list = []\n",
    "    for i in range(30000):\n",
    "        i += 1\n",
    "\n",
    "        output_y = model(train_features)\n",
    "        # 计算损失\n",
    "        loss = criterion(output_y, train_labels)\n",
    "\n",
    "        # 2 反向传播\n",
    "        # 梯度要清0\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        # 更新权重参数\n",
    "        optimizer.step()\n",
    "\n",
    "        # 打印\n",
    "        if i % 100 == 0:\n",
    "            print(\"迭代次数：%d,  loss值：%.8f\" % (i, loss.item()))\n",
    "            loss_list.append(loss.item())\n",
    "\n",
    "    # 测试模式\n",
    "    model.eval()\n",
    "    predict = model(train_features).data.numpy()\n",
    "\n",
    "    plt.plot(predict, \"ro\")\n",
    "    plt.plot(train_labels, \"k\")\n",
    "    plt.show()\n",
    "\n",
    "    plt.plot(loss_list)\n",
    "    plt.show()\n",
    "    plt.show()\n",
    "\n",
    "    predict_price = predict * train_labels_std + train_labels_mean\n",
    "    plt.plot(predict_price[0:100], \"r\")\n",
    "    plt.plot(train_data.SalePrice.values[0:100], \"k\")\n",
    "    plt.show()\n",
    "\n",
    "    # 假设训练集和测试集同分布\n",
    "    test_result = model(test_features).detach().numpy() * train_labels_std + train_labels_mean\n",
    "\n",
    "    plt.plot(test_result, \"k\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "迭代次数：100,  loss值：0.73722738\n",
      "迭代次数：200,  loss值：0.51884604\n",
      "迭代次数：300,  loss值：0.38919964\n",
      "迭代次数：400,  loss值：0.31329051\n",
      "迭代次数：500,  loss值：0.26747677\n",
      "迭代次数：600,  loss值：0.23759070\n",
      "迭代次数：700,  loss值：0.21623522\n",
      "迭代次数：800,  loss值：0.19986141\n",
      "迭代次数：900,  loss值：0.18675528\n",
      "迭代次数：1000,  loss值：0.17600428\n",
      "迭代次数：1100,  loss值：0.16704775\n",
      "迭代次数：1200,  loss值：0.15949647\n",
      "迭代次数：1300,  loss值：0.15305996\n",
      "迭代次数：1400,  loss值：0.14751449\n",
      "迭代次数：1500,  loss值：0.14268616\n",
      "迭代次数：1600,  loss值：0.13843967\n",
      "迭代次数：1700,  loss值：0.13467000\n",
      "迭代次数：1800,  loss值：0.13129565\n",
      "迭代次数：1900,  loss值：0.12825328\n",
      "迭代次数：2000,  loss值：0.12549330\n",
      "迭代次数：2100,  loss值：0.12297662\n",
      "迭代次数：2200,  loss值：0.12067195\n",
      "迭代次数：2300,  loss值：0.11855392\n",
      "迭代次数：2400,  loss值：0.11660155\n",
      "迭代次数：2500,  loss值：0.11479720\n",
      "迭代次数：2600,  loss值：0.11312579\n",
      "迭代次数：2700,  loss值：0.11157420\n",
      "迭代次数：2800,  loss值：0.11013092\n",
      "迭代次数：2900,  loss值：0.10878571\n",
      "迭代次数：3000,  loss值：0.10752948\n",
      "迭代次数：3100,  loss值：0.10635404\n",
      "迭代次数：3200,  loss值：0.10525204\n",
      "迭代次数：3300,  loss值：0.10421694\n",
      "迭代次数：3400,  loss值：0.10324285\n",
      "迭代次数：3500,  loss值：0.10232450\n",
      "迭代次数：3600,  loss值：0.10145718\n",
      "迭代次数：3700,  loss值：0.10063671\n",
      "迭代次数：3800,  loss值：0.09985933\n",
      "迭代次数：3900,  loss值：0.09912170\n",
      "迭代次数：4000,  loss值：0.09842083\n",
      "迭代次数：4100,  loss值：0.09775403\n",
      "迭代次数：4200,  loss值：0.09711888\n",
      "迭代次数：4300,  loss值：0.09651318\n",
      "迭代次数：4400,  loss值：0.09593496\n",
      "迭代次数：4500,  loss值：0.09538238\n",
      "迭代次数：4600,  loss值：0.09485380\n",
      "迭代次数：4700,  loss值：0.09434767\n",
      "迭代次数：4800,  loss值：0.09386256\n",
      "迭代次数：4900,  loss值：0.09339717\n",
      "迭代次数：5000,  loss值：0.09295028\n",
      "迭代次数：5100,  loss值：0.09252075\n",
      "迭代次数：5200,  loss值：0.09210753\n",
      "迭代次数：5300,  loss值：0.09170965\n",
      "迭代次数：5400,  loss值：0.09132619\n",
      "迭代次数：5500,  loss值：0.09095632\n",
      "迭代次数：5600,  loss值：0.09059924\n",
      "迭代次数：5700,  loss值：0.09025421\n",
      "迭代次数：5800,  loss值：0.08992059\n",
      "迭代次数：5900,  loss值：0.08959772\n",
      "迭代次数：6000,  loss值：0.08928504\n",
      "迭代次数：6100,  loss值：0.08898200\n",
      "迭代次数：6200,  loss值：0.08868811\n",
      "迭代次数：6300,  loss值：0.08840288\n",
      "迭代次数：6400,  loss值：0.08812588\n",
      "迭代次数：6500,  loss值：0.08785672\n",
      "迭代次数：6600,  loss值：0.08759498\n",
      "迭代次数：6700,  loss值：0.08734030\n",
      "迭代次数：6800,  loss值：0.08709234\n",
      "迭代次数：6900,  loss值：0.08685077\n",
      "迭代次数：7000,  loss值：0.08661525\n",
      "迭代次数：7100,  loss值：0.08638549\n",
      "迭代次数：7200,  loss值：0.08616117\n",
      "迭代次数：7300,  loss值：0.08594204\n",
      "迭代次数：7400,  loss值：0.08572780\n",
      "迭代次数：7500,  loss值：0.08551817\n",
      "迭代次数：7600,  loss值：0.08531292\n",
      "迭代次数：7700,  loss值：0.08511177\n",
      "迭代次数：7800,  loss值：0.08491453\n",
      "迭代次数：7900,  loss值：0.08472092\n",
      "迭代次数：8000,  loss值：0.08453076\n",
      "迭代次数：8100,  loss值：0.08434382\n",
      "迭代次数：8200,  loss值：0.08415992\n",
      "迭代次数：8300,  loss值：0.08397886\n",
      "迭代次数：8400,  loss值：0.08380051\n",
      "迭代次数：8500,  loss值：0.08362468\n",
      "迭代次数：8600,  loss值：0.08345123\n",
      "迭代次数：8700,  loss值：0.08328006\n",
      "迭代次数：8800,  loss值：0.08311102\n",
      "迭代次数：8900,  loss值：0.08294404\n",
      "迭代次数：9000,  loss值：0.08277898\n",
      "迭代次数：9100,  loss值：0.08261581\n",
      "迭代次数：9200,  loss值：0.08245442\n",
      "迭代次数：9300,  loss值：0.08229478\n",
      "迭代次数：9400,  loss值：0.08213682\n",
      "迭代次数：9500,  loss值：0.08198051\n",
      "迭代次数：9600,  loss值：0.08182580\n",
      "迭代次数：9700,  loss值：0.08167267\n",
      "迭代次数：9800,  loss值：0.08152112\n",
      "迭代次数：9900,  loss值：0.08137112\n",
      "迭代次数：10000,  loss值：0.08122266\n",
      "迭代次数：10100,  loss值：0.08107574\n",
      "迭代次数：10200,  loss值：0.08093031\n",
      "迭代次数：10300,  loss值：0.08078640\n",
      "迭代次数：10400,  loss值：0.08064403\n",
      "迭代次数：10500,  loss值：0.08050317\n",
      "迭代次数：10600,  loss值：0.08036387\n",
      "迭代次数：10700,  loss值：0.08022612\n",
      "迭代次数：10800,  loss值：0.08008992\n",
      "迭代次数：10900,  loss值：0.07995529\n",
      "迭代次数：11000,  loss值：0.07982219\n",
      "迭代次数：11100,  loss值：0.07969064\n",
      "迭代次数：11200,  loss值：0.07956064\n",
      "迭代次数：11300,  loss值：0.07943218\n",
      "迭代次数：11400,  loss值：0.07930528\n",
      "迭代次数：11500,  loss值：0.07917989\n",
      "迭代次数：11600,  loss值：0.07905605\n",
      "迭代次数：11700,  loss值：0.07893370\n",
      "迭代次数：11800,  loss值：0.07881286\n",
      "迭代次数：11900,  loss值：0.07869352\n",
      "迭代次数：12000,  loss值：0.07857569\n",
      "迭代次数：12100,  loss值：0.07845932\n",
      "迭代次数：12200,  loss值：0.07834442\n",
      "迭代次数：12300,  loss值：0.07823097\n",
      "迭代次数：12400,  loss值：0.07811897\n",
      "迭代次数：12500,  loss值：0.07800844\n",
      "迭代次数：12600,  loss值：0.07789918\n",
      "迭代次数：12700,  loss值：0.07779137\n",
      "迭代次数：12800,  loss值：0.07768495\n",
      "迭代次数：12900,  loss值：0.07757995\n",
      "迭代次数：13000,  loss值：0.07747628\n",
      "迭代次数：13100,  loss值：0.07737400\n",
      "迭代次数：13200,  loss值：0.07727301\n",
      "迭代次数：13300,  loss值：0.07717326\n",
      "迭代次数：13400,  loss值：0.07707480\n",
      "迭代次数：13500,  loss值：0.07697760\n",
      "迭代次数：13600,  loss值：0.07688163\n",
      "迭代次数：13700,  loss值：0.07678688\n",
      "迭代次数：13800,  loss值：0.07669331\n",
      "迭代次数：13900,  loss值：0.07660093\n",
      "迭代次数：14000,  loss值：0.07650971\n",
      "迭代次数：14100,  loss值：0.07641956\n",
      "迭代次数：14200,  loss值：0.07633053\n",
      "迭代次数：14300,  loss值：0.07624255\n",
      "迭代次数：14400,  loss值：0.07615560\n",
      "迭代次数：14500,  loss值：0.07606971\n",
      "迭代次数：14600,  loss值：0.07598475\n",
      "迭代次数：14700,  loss值：0.07590079\n",
      "迭代次数：14800,  loss值：0.07581774\n",
      "迭代次数：14900,  loss值：0.07573560\n",
      "迭代次数：15000,  loss值：0.07565445\n",
      "迭代次数：15100,  loss值：0.07557384\n",
      "迭代次数：15200,  loss值：0.07549416\n",
      "迭代次数：15300,  loss值：0.07541521\n",
      "迭代次数：15400,  loss值：0.07533702\n",
      "迭代次数：15500,  loss值：0.07525948\n",
      "迭代次数：15600,  loss值：0.07518257\n",
      "迭代次数：15700,  loss值：0.07510627\n",
      "迭代次数：15800,  loss值：0.07503059\n",
      "迭代次数：15900,  loss值：0.07495547\n",
      "迭代次数：16000,  loss值：0.07488088\n",
      "迭代次数：16100,  loss值：0.07480679\n",
      "迭代次数：16200,  loss值：0.07473320\n",
      "迭代次数：16300,  loss值：0.07466011\n",
      "迭代次数：16400,  loss值：0.07458749\n",
      "迭代次数：16500,  loss值：0.07451528\n",
      "迭代次数：16600,  loss值：0.07444352\n",
      "迭代次数：16700,  loss值：0.07437217\n",
      "迭代次数：16800,  loss值：0.07430147\n",
      "迭代次数：16900,  loss值：0.07423079\n",
      "迭代次数：17000,  loss值：0.07416078\n",
      "迭代次数：17100,  loss值：0.07409113\n",
      "迭代次数：17200,  loss值：0.07402191\n",
      "迭代次数：17300,  loss值：0.07395311\n",
      "迭代次数：17400,  loss值：0.07388476\n",
      "迭代次数：17500,  loss值：0.07381681\n",
      "迭代次数：17600,  loss值：0.07374927\n",
      "迭代次数：17700,  loss值：0.07368214\n",
      "迭代次数：17800,  loss值：0.07361542\n",
      "迭代次数：17900,  loss值：0.07354912\n",
      "迭代次数：18000,  loss值：0.07348321\n",
      "迭代次数：18100,  loss值：0.07341774\n",
      "迭代次数：18200,  loss值：0.07335266\n",
      "迭代次数：18300,  loss值：0.07328801\n",
      "迭代次数：18400,  loss值：0.07322379\n",
      "迭代次数：18500,  loss值：0.07315998\n",
      "迭代次数：18600,  loss值：0.07309654\n",
      "迭代次数：18700,  loss值：0.07303352\n",
      "迭代次数：18800,  loss值：0.07297091\n",
      "迭代次数：18900,  loss值：0.07290871\n",
      "迭代次数：19000,  loss值：0.07284693\n",
      "迭代次数：19100,  loss值：0.07278562\n",
      "迭代次数：19200,  loss值：0.07272456\n",
      "迭代次数：19300,  loss值：0.07266394\n",
      "迭代次数：19400,  loss值：0.07260372\n",
      "迭代次数：19500,  loss值：0.07254390\n",
      "迭代次数：19600,  loss值：0.07248450\n",
      "迭代次数：19700,  loss值：0.07242559\n",
      "迭代次数：19800,  loss值：0.07236683\n",
      "迭代次数：19900,  loss值：0.07230859\n",
      "迭代次数：20000,  loss值：0.07225068\n",
      "迭代次数：20100,  loss值：0.07219321\n",
      "迭代次数：20200,  loss值：0.07213610\n",
      "迭代次数：20300,  loss值：0.07207941\n",
      "迭代次数：20400,  loss值：0.07202309\n",
      "迭代次数：20500,  loss值：0.07196710\n",
      "迭代次数：20600,  loss值：0.07191150\n",
      "迭代次数：20700,  loss值：0.07185633\n",
      "迭代次数：20800,  loss值：0.07180142\n",
      "迭代次数：20900,  loss值：0.07174687\n",
      "迭代次数：21000,  loss值：0.07169271\n",
      "迭代次数：21100,  loss值：0.07163907\n",
      "迭代次数：21200,  loss值：0.07158548\n",
      "迭代次数：21300,  loss值：0.07153239\n",
      "迭代次数：21400,  loss值：0.07147965\n",
      "迭代次数：21500,  loss值：0.07142723\n",
      "迭代次数：21600,  loss值：0.07137523\n",
      "迭代次数：21700,  loss值：0.07132338\n",
      "迭代次数：21800,  loss值：0.07127196\n",
      "迭代次数：21900,  loss值：0.07122093\n",
      "迭代次数：22000,  loss值：0.07117023\n",
      "迭代次数：22100,  loss值：0.07111986\n",
      "迭代次数：22200,  loss值：0.07106978\n",
      "迭代次数：22300,  loss值：0.07102005\n",
      "迭代次数：22400,  loss值：0.07097089\n",
      "迭代次数：22500,  loss值：0.07092157\n",
      "迭代次数：22600,  loss值：0.07087278\n",
      "迭代次数：22700,  loss值：0.07082436\n",
      "迭代次数：22800,  loss值：0.07077631\n",
      "迭代次数：22900,  loss值：0.07072852\n",
      "迭代次数：23000,  loss值：0.07068107\n",
      "迭代次数：23100,  loss值：0.07063393\n",
      "迭代次数：23200,  loss值：0.07058709\n",
      "迭代次数：23300,  loss值：0.07054059\n",
      "迭代次数：23400,  loss值：0.07049444\n",
      "迭代次数：23500,  loss值：0.07044861\n",
      "迭代次数：23600,  loss值：0.07040309\n",
      "迭代次数：23700,  loss值：0.07035790\n",
      "迭代次数：23800,  loss值：0.07031304\n",
      "迭代次数：23900,  loss值：0.07026847\n",
      "迭代次数：24000,  loss值：0.07022423\n",
      "迭代次数：24100,  loss值：0.07018038\n",
      "迭代次数：24200,  loss值：0.07013679\n",
      "迭代次数：24300,  loss值：0.07009352\n",
      "迭代次数：24400,  loss值：0.07005060\n",
      "迭代次数：24500,  loss值：0.07000796\n",
      "迭代次数：24600,  loss值：0.06996563\n",
      "迭代次数：24700,  loss值：0.06992368\n",
      "迭代次数：24800,  loss值：0.06988196\n",
      "迭代次数：24900,  loss值：0.06984062\n",
      "迭代次数：25000,  loss值：0.06979971\n",
      "迭代次数：25100,  loss值：0.06975887\n",
      "迭代次数：25200,  loss值：0.06971845\n",
      "迭代次数：25300,  loss值：0.06967834\n",
      "迭代次数：25400,  loss值：0.06963857\n",
      "迭代次数：25500,  loss值：0.06959914\n",
      "迭代次数：25600,  loss值：0.06956004\n",
      "迭代次数：25700,  loss值：0.06952114\n",
      "迭代次数：25800,  loss值：0.06948263\n",
      "迭代次数：25900,  loss值：0.06944443\n",
      "迭代次数：26000,  loss值：0.06940655\n",
      "迭代次数：26100,  loss值：0.06936900\n",
      "迭代次数：26200,  loss值：0.06933171\n",
      "迭代次数：26300,  loss值：0.06929474\n",
      "迭代次数：26400,  loss值：0.06925810\n",
      "迭代次数：26500,  loss值：0.06922179\n",
      "迭代次数：26600,  loss值：0.06918577\n",
      "迭代次数：26700,  loss值：0.06915005\n",
      "迭代次数：26800,  loss值：0.06911463\n",
      "迭代次数：26900,  loss值：0.06907951\n",
      "迭代次数：27000,  loss值：0.06904474\n",
      "迭代次数：27100,  loss值：0.06901024\n",
      "迭代次数：27200,  loss值：0.06897609\n",
      "迭代次数：27300,  loss值：0.06894220\n",
      "迭代次数：27400,  loss值：0.06890861\n",
      "迭代次数：27500,  loss值：0.06887535\n",
      "迭代次数：27600,  loss值：0.06884243\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "迭代次数：27700,  loss值：0.06880980\n",
      "迭代次数：27800,  loss值：0.06877746\n",
      "迭代次数：27900,  loss值：0.06874536\n",
      "迭代次数：28000,  loss值：0.06871362\n",
      "迭代次数：28100,  loss值：0.06868219\n",
      "迭代次数：28200,  loss值：0.06865110\n",
      "迭代次数：28300,  loss值：0.06862031\n",
      "迭代次数：28400,  loss值：0.06858964\n",
      "迭代次数：28500,  loss值：0.06855940\n",
      "迭代次数：28600,  loss值：0.06852946\n",
      "迭代次数：28700,  loss值：0.06849978\n",
      "迭代次数：28800,  loss值：0.06847046\n",
      "迭代次数：28900,  loss值：0.06844143\n",
      "迭代次数：29000,  loss值：0.06841266\n",
      "迭代次数：29100,  loss值：0.06838419\n",
      "迭代次数：29200,  loss值：0.06835598\n",
      "迭代次数：29300,  loss值：0.06832813\n",
      "迭代次数：29400,  loss值：0.06830058\n",
      "迭代次数：29500,  loss值：0.06827327\n",
      "迭代次数：29600,  loss值：0.06824625\n",
      "迭代次数：29700,  loss值：0.06821954\n",
      "迭代次数：29800,  loss值：0.06819313\n",
      "迭代次数：29900,  loss值：0.06816695\n",
      "迭代次数：30000,  loss值：0.06814107\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_and_test()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}