编辑代码

# coding:utf-8
#JSRUN引擎2.0，支持多达30种语言在线运行，全仿真在线交互输入输出。 
print("Hello world!   -  python.jsrun.net .")

from sklearn.model_selection import train_test_split
from sklearn import datasets
from sklearn.neighbors import KNeighborsClassifier
import numpy as np

# 加载数据集
iris = datasets.load_iris()
x = iris.data  # 4维特征数据
y = iris.target  # 分类标签

# 划分训练测试集(70%训练,30%测试)
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=42)

# 创建KNN分类器(K=3)
knn = KNeighborsClassifier(n_neighbors=3)
knn.fit(x_train, y_train)

# 预测并评估
predictions = knn.predict(x_test)
print(predictions)
print(y_test)