网格搜索和交叉验证 SVM

Question

我正在使用网格搜索的最佳参数对 10 倍交叉验证实施支持向量机，我需要了解预测结果为什么不同我在训练集上得到了两个准确度结果测试通知我需要训练集上最佳参数的预测结果以供进一步分析代码和结果如下所述。任何解释from __future__ import print_functionfrom sklearn import datasetsfrom sklearn.model_selection import train_test_splitfrom sklearn.model_selection import GridSearchCVfrom sklearn.metrics import classification_reportfrom sklearn.svm import SVCfrom sklearn.metrics import accuracy_scorefrom time import *from sklearn import metricsX=datascaled.iloc[:,0:13]y=datascaled['num']np.random.seed(1)# Split the dataset in two equal partsX_train, X_test, y_train, y_test = train_test_split(    X, y, test_size=0.3, random_state=0)# Set the parameters by cross-validationtuned_parameters =  [{'kernel': ['rbf'], 'gamma': [1e-2, 1e-3, 1e-4, 1e-5],                     'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000]},                    {'kernel': ['sigmoid'], 'gamma': [1e-2, 1e-3, 1e-4, 1e-5],                     'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000] },{'kernel': ['linear'], 'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000]}]              print()clf = GridSearchCV(SVC(), tuned_parameters, cv=10,                       scoring='accuracy')t0 = time()clf.fit(X_train, y_train)t = time() - t0print("Best parameters set found on development set:")print()print(clf.best_params_)print()print('Training accuracy')print(clf.best_score_)print(clf.best_estimator_)print()print()print('****Results****')svm_pred=clf.predict(X_train)#print("\t\taccuracytrainkfold: {}".format(metrics.accuracy_score(y_train, svm_pred)))print("=" * 52)print("time cost: {}".format(t))print()print("confusion matrix\n", metrics.confusion_matrix(y_train, svm_pred))print()print("\t\taccuracy: {}".format(metrics.accuracy_score(y_train, svm_pred)))print("\t\troc_auc_score: {}".format(metrics.roc_auc_score(y_train, svm_pred)))print("\t\tcohen_kappa_score: {}".format(metrics.cohen_kappa_score(y_train, svm_pred)))print()