Add OptunaSearchCV with terminator

terminator/terminator_search_cv.py

@@ -0,0 +1,37 @@
+"""
+Optuna example that optimizes a classifier configuration using OptunaSearchCV.
+
+This example is the same as `sklearn/sklearn_optuna_search_cv_simple.py` except
+that you leave termination of the study up to the terminator callback.
+"""
+
+import optuna
+from optuna.terminator import TerminatorCallback
+
+from sklearn.datasets import load_iris
+from sklearn.svm import SVC
+
+
+if __name__ == "__main__":
+    clf = SVC(gamma="auto")
+
+    param_distributions = {
+        "C": optuna.distributions.FloatDistribution(1e-10, 1e10, log=True),
+        "degree": optuna.distributions.IntDistribution(1, 5),
+    }
+    terminator = TerminatorCallback()
+
+    optuna_search = optuna.integration.OptunaSearchCV(
+        clf, param_distributions, n_trials=100, timeout=600, verbose=2, callbacks=[terminator]
+    )
+
+    X, y = load_iris(return_X_y=True)
+    optuna_search.fit(X, y)
+
+    print("Best trial:")
+    trial = optuna_search.study_.best_trial
+
+    print("  Value: ", trial.value)
+    print("  Params: ")
+    for key, value in trial.params.items():
+        print("    {}: {}".format(key, value))