D26 新增特徵組合後，線性迴歸 / 梯度提升樹比率變化問題

df['distance_real'] = # 我加入的新特徵
train_X = scaler.fit_transform(df)
print('Linear Reg Score : %s' % cross_val_score(Linear, train_X, train_Y, cv=5).mean())
print('Gradient Boosting Reg Score : %s' % cross_val_score(GDBT, train_X, train_Y, cv=5).mean())

'''output'''
Linear Reg Score : 0.030082856712116544
Gradient Boosting Reg Score : 0.8018675477066125

df['distance_real'] = # 我加入的新特徵
train_X = scaler.fit_transform(df)
print('Linear Reg Score : %s' % cross_val_score(Linear, train_X, train_Y, cv=5).mean())
print('Gradient Boosting Reg Score : %s' % cross_val_score(GDBT, train_X, train_Y, cv=5).mean())

'''output'''
Linear Reg Score : 0.030082856712116544
Gradient Boosting Reg Score : 0.8018675477066125