從最佳子集中獲取最佳變量回歸R

Question

我想對一組變量運行最佳子集迴歸，然後使用R獲得最佳3個變量。我在獲取最佳2個變量時遇到了問題。我已經在下面包含了我的代碼。

set.seed(10) 

a <- 1:100 
b <- 1:100 
c <- 1:100 
d <- 1:100 
e <- 1:100 
f <- 1:100 
g <- 1:100 
h <- 1:100 

data <- data.frame(a, b, c, d, e, f, g, h) 

library(leaps) 

# best subsets regression 
test <- regsubsets(a ~ b + c + d + e + f + g + h, data=data, nbest=4) 
# nbest = 4, is the number of subsets of each size that is reported 

# plot a table of models showing variables in each model. 
summary(test) 

# models are ordered by the selection statistic. 
plot(test,scale="r2") 

#get the variables that are important to the model 
coef(test, 2) 

#NOTE: THIS DOESN'T GIVE ME THE 2 BEST VARIABLES. IT ONLY GIVES ME THE BEST VARIABLE AT THE 2ND ITERATION. LOOK AT: 
coef(test, 1:2) 

您的幫助將不勝感激！

最佳， 達納

Answer 1

考慮用一個例子內置mtcars數據集：

test <- regsubsets(mpg ~ ., data = mtcars, nbest = 4) 

這是從summary(test)輸出：被佈置

summary(test) 
# Subset selection object 
# Call: regsubsets.formula(mpg ~ ., data = mtcars, nbest = 4) 
# 10 Variables (and intercept) 
# <..snip..> 
# 4 subsets of each size up to 8 
# Selection Algorithm: exhaustive 
#   cyl disp hp drat wt qsec vs am gear carb 
# 1 (1) " " " " " " " " "*" " " " " " " " " " " 
# 1 (2) "*" " " " " " " " " " " " " " " " " " " 
# 1 (3) " " "*" " " " " " " " " " " " " " " " " 
# 1 (4) " " " " "*" " " " " " " " " " " " " " " 
# 2 (1) "*" " " " " " " "*" " " " " " " " " " " 
# 2 (2) " " " " "*" " " "*" " " " " " " " " " " 
# 2 (3) " " " " " " " " "*" "*" " " " " " " " " 
# 2 (4) " " " " " " " " "*" " " "*" " " " " " " 
# 3 (1) " " " " " " " " "*" "*" " " "*" " " " " 
# <..snip..> 

係數組由獨立變量的數量，在4的子集（我們用表示論證）;因此，coef(test, 1:4)將返回來自具有一個自變量的模型的係數，coef(test, 5:8)將是具有兩個自變量的那些，依此類推。在每個子集中，「最佳」模型首先出現。因此，具有兩個自變量的「最佳」模型將成爲模型5：

coef(test, 5) 
# (Intercept)   cyl   wt 
# 39.686261 -1.507795 -3.190972