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)