marketing_predict.py 文件源码

def svm_clf(data):
    clf = svm.LinearSVC(C=1)
    for i in range(5):
        scores = cross_val_score(clf, data.X_train, data.y_train, cv=10)
        print("iteration",i, "svm mean:", scores.mean())
        scores = list(scores)
        print("svm train scores:\n", scores)
    return clf


# use knn for impute missing values