util.py 文件源码

def svc_classify(my_train_data, my_train_label, my_test_data, svc_c):
    # clf = svm.SVC(C=svc_c, kernel='poly')
    clf = svm.SVC(C=svc_c)
    scores = cross_validation.cross_val_score(clf, my_train_data, my_train_label, cv=5)
    print("svc(C=%.1f) accuracy: %0.3f (+/- %0.3f)" % (svc_c, scores.mean(), scores.std() * 2))
    clf.fit(my_train_data, my_train_label)
    my_test_label = clf.predict(my_test_data)
    file_name = "svc_%.1f.csv" % svc_c
    save_data(my_test_label, file_name)