October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Content preview from 数据科学中的实用统计学(第2版)
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140
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第
4
章
update(step_lm, . ~ . - SqFtTotLiving - SqFtFinBasement - Bathrooms)
Call:
lm(formula = AdjSalePrice ~ Bedrooms + BldgGrade + PropertyType +
YrBuilt, data = house, na.action = na.omit)
Coefficients:
(Intercept) Bedrooms
4913973 27151
BldgGrade PropertyTypeSingle Family
248998 -19898
PropertyTypeTownhouse YrBuilt
-47355 -3212
可以使用
update
函数为模型添加或删除变量。现在卧室的系数是正的了——和预期一致
（由于与房屋面积有关的变量都被删除了，它实际上只是房屋面积的一个代理变量）。
在
Python
中
，没有与
R
语言中
update
函数相同功能的函数，我们需要使用修改后的预测
变量列表重新拟合模型：
predictors = ['Bedrooms', 'BldgGrade', 'PropertyType', 'YrBuilt']
outcome = 'AdjSalePrice'
X = pd.get_dummies(house[predictors], drop_first=True)
reduced_lm = LinearRegression()
reduced_lm.fit(X, ...
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