svm基础模型搭建

def SVM_Classifier(train, trainLabel,test):

    clf = svm.SVC(C=1, kernel='rbf', degree=3, gamma='auto', coef0=0.0, shrinking=True,\
                  probability=False, tol=0.001,cache_size=200, class_weight=None, verbose=1,\
                  max_iter=-1,decision_function_shape='ovr', random_state=None)


    clf.fit(train, trainLabel)
    # 在拟合后，这个模型可以用来预测新的分类值
    pred = clf.predict(test)


    return pred