CCIT.py 文件源码

def cross_validate(classifier, n_folds = 5):
    '''Custom cross-validation module I always use '''
    train_X = classifier['train_X']
    train_y = classifier['train_y']
    model = classifier['model']
    score = 0.0

    skf = KFold(n_splits = n_folds)
    for train_index, test_index in skf.split(train_X):
        X_train, X_test = train_X[train_index], train_X[test_index]
        y_train, y_test = train_y[train_index], train_y[test_index]
        clf = model.fit(X_train,y_train)
        pred = clf.predict_proba(X_test)[:,1]
        #print 'cross', roc_auc_score(y_test,pred)
        score = score + roc_auc_score(y_test,pred)

    return score/n_folds