其实最好自己敲一遍

def main():
    from sklearn.datasets import load_iris
    iris = load_iris()
    print(iris)
    print(len(iris["data"]))
    from sklearn.model_selection import train_test_split
    train_data,test_data,train_target,test_target=train_test_split(iris.data,iris.target,test_size=0.2,random_state=1)

    from sklearn import tree
    #决策树
    clf = tree.DecisionTreeClassifier(criterion="entropy")
    clf.fit(train_data,train_target)
    y_pred = clf.predict(test_data)

    #Verify
    from sklearn import metrics
    print(metrics.accuracy_score(y_true=test_target,y_pred=y_pred))
    print(metrics.confusion_matrix(y_true=test_target,y_pred=y_pred))
    with open("D:/test/test.xlsx","w") as f:
        tree.export_graphviz(clf,out_file=f)
if __name__=="__main__":
    main()

自己敲一遍