# Ideone机器学习实验 - 基础版
import numpy as np
from sklearn.linear_model import LinearRegression
 
print("🎯 Ideone线性回归实验")
 
# 生成数据
X = np.array([1, 2, 3, 4, 5]).reshape(-1, 1)
y = np.array([2, 4, 6, 8, 10])
 
# 训练模型
model = LinearRegression()
model.fit(X, y)
 
# 输出结果
print(f"斜率: {model.coef_[0]}")
print(f"截距: {model.intercept_}")
print(f"R²得分: {model.score(X, y)}")
print("✅ 简单线性回归完成")

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