我嘗試在標準數據集“iris.csv”中進行預測import pandas as pdfrom sklearn import treedf = pd.read_csv('iris.csv')df.columns = ['X1', 'X2', 'X3', 'X4', 'Y']df.head()# Decision treefrom sklearn.model_selection import train_test_splitdecision = tree.DecisionTreeClassifier(criterion='gini')X = df.values[:, 0:4]Y = df.values[:, 4]trainX, testX, trainY, testY = train_test_split(X, Y, test_size=0.25)decision.fit(trainX, trainY)y_score = decision.score(testX, testY)print('Accuracy: ', y_score)# Compute the average precision scorefrom sklearn.metrics import average_precision_scoreaverage_precision = average_precision_score(testY, y_score)print('Average precision-recall score: {0:0.2f}'.format(      average_precision))我有 valueerrorFile "C:/Users/Ultra/PycharmProjects/poker_ML/decision_tree.py", line 20, in <module>    average_precision = average_precision_score(testY, y_score)  File "C:\Users\Ultra\PycharmProjects\poker_ML\venv\lib\site-packages\sklearn\metrics\ranking.py", line 241, in average_precision_score    average, sample_weight=sample_weight)  File "C:\Users\Ultra\PycharmProjects\poker_ML\venv\lib\site-packages\sklearn\metrics\base.py", line 74, in _average_binary_score    raise ValueError("{0} format is not supported".format(y_type))ValueError: multiclass format is not supported如何計算 3 類的精確召回率？sklearn 中決策樹的精確召回是如何工作的。也許我在計算“y_score”時有錯誤？