from sklearn.datasets import load_iris
    from sklearn.model_selection import train_test_split
    from sklearn.neighbors import KNeighborsClassifier
    # 加载数据
    iris = load_iris()
    X = iris.data
    y = iris.target
    print(iris.data.shape,iris.target.shape)
    # 分割数据
    X_train,X_test,y_train,y_test=train_test_split(iris.data,iris.target,test_size=0.4,random_state=0)
    print(X_train.shape,y_train.shape)
    print(X_test.shape,y_test.shape)
    # 建立模型
    knn = KNeighborsClassifier()
    # 训练模型
    knn.fit(X_train,y_train)
    # 预测模型
    y_pred = knn.predict(X_test)
    # 输出
    print("y_test: ",y_test)
    print("y_pred: ",y_pred)
    print("y_pred-y_test: ",y_pred-y_test)