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@@ -25,13 +25,13 @@ from sklearn.model_selection import KFold, cross_val_score
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def _get_best_model(X_train, y_train):
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- Cs = [0.01, 0.1, 10, 100, 1000]
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- gammas = [0.01, 0.1, 10, 100]
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+ Cs = [0.001, 0.01, 0.1, 1, 5, 10, 100, 1000]
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+ gammas = [0.001, 0.01, 0.1, 1, 5, 10, 100, 1000]
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param_grid = {'kernel':['rbf'], 'C': Cs, 'gamma' : gammas}
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svc = svm.SVC(probability=True, class_weight='balanced')
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#clf = GridSearchCV(svc, param_grid, cv=5, verbose=1, scoring=my_accuracy_scorer, n_jobs=-1)
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- clf = GridSearchCV(svc, param_grid, cv=5, verbose=1, n_jobs=-1)
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+ clf = GridSearchCV(svc, param_grid, cv=10, verbose=2, n_jobs=-1)
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clf.fit(X_train, y_train)
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