我正在使用skilearn進行SVM培訓.我正在使用交叉驗證來評估估算器并避免過度擬合模型.

我將數據分成兩部分.訓練數據和測試數據.這是代碼：

import numpy as np

from sklearn import cross_validation

from sklearn import datasets

from sklearn import svm

X_train, X_test, y_train, y_test = cross_validation.train_test_split(

iris.data, iris.target, test_size=0.4, random_state=0

)

clf = svm.SVC(kernel='linear', C=1)

scores = cross_validation.cross_val_score(clf, X_train, y_train, cv=5)

print scores

# Now I need to evaluate the estimator *clf* on X_test.

clf.score(X_test,y_test)

# here, I get an error say that the model is not fitted using fit(), but normally,

# in cross_val_score function the model is fitted? What is the problem?

總結

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