Predict() with regsubsets

Question

I'm trying to replicate the results from An Introduction to Statistical Learning with Applications in R. Specifically, the Lab in section 6.5.3. I have followed the code in the lab exactly:

library("ISLR")
library("leaps")
set.seed(1)
train = sample(c(TRUE, FALSE), nrow(Hitters), rep = TRUE)
test = (!train)
regfit.best = regsubsets(Salary ~., data = Hitters[train,], nvmax= 19)

test.mat = model.matrix(Salary~., data = Hitters[test,]) 

val.errors = rep(NA, 19)
for (i in 1:19){
  coefi= coef(regfit.best, id = i)
  pred=test.mat[,names(coefi)]%*%coefi
  val.errors[i]=mean((Hitters$Salary[test]-pred)^2) 
}

When I run this I still get the following error:

Warning message:
In Hitters$Salary[test] - pred :
  longer object length is not a multiple of shorter object length
Error in mean((Hitters$Salary[test] - pred)^2) : 
  error in evaluating the argument 'x' in selecting a method for function 'mean': Error: dims [product 121] do not match the length of object [148]

And val.errors is a vector of 19 NAs.

I'm still relatively new to R and to the validation approach, so I'm not sure exactly why the dimensions of these are different.

Answer 1

这实际上是一个问题，没有从前一小节继承步骤，省略了不完整的条目。

Answer 2

您需要删除缺少数据的行。首先运行“ Hitters = na.omit（Hitters）”。