分类报告中少数类别的准确度、召回率和F1分数均为零

我在使用SkLearn包中的SVM和MLP分类器时出错。错误为C:\Users\cse_s\anaconda3\lib\site packages\sklearn\metrics_classification.py:1327:未定义度量警告：精度和F分数定义错误，在没有预测样本的标签中设置为0.0。使用zero_division参数控制此行为_warn_prf（平均值，修饰符，消息开始，长度（结果））

用于拆分数据集的代码

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y)

SVM分类器代码

from sklearn import svm
SVM_classifier = svm.SVC(kernel="rbf", probability = True, random_state=1)
SVM_classifier.fit(X_train, y_train)
SVM_y_pred = SVM_classifier.predict(X_test)
print(classification_report(y_test, SVM_y_pred))

MLP分类器代码

from sklearn.neural_network import MLPClassifier
MLP = MLPClassifier(random_state=1, learning_rate = "constant", learning_rate_init=0.3, momentum = 0.2 )
MLP.fit(X_train, y_train)
R_y_pred = MLP.predict(X_test)
target_names = ['No class', 'Yes Class']
print(classification_report(y_test, R_y_pred, target_names=target_names))

两个分类器的错误相同