short formula call for many variables when building a model [duplicate]

Question

I am trying to build a regression model with lm(...). My dataset has lots of features( >50). I do not want to write my code as:

lm(output ~ feature1 + feature2 + feature3 + ... + feature70) 

I was wondering what is the short hand notation to write this code?

Answer 1

You can use . as described in the help page for formula. The . stands for "all columns not otherwise in the formula".

lm(output ~ ., data = myData).

Alternatively, construct the formula manually with paste. This example is from the as.formula() help page:

xnam <- paste("x", 1:25, sep="") (fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+")))) 

You can then insert this object into regression function: lm(fmla, data = myData).

Answer 2

Could also try things like:

lm(output ~ myData[,2:71], data=myData) 

Assuming output is the first column feature1:feature70 are the next 70 columns.

Or

features <- paste("feature",1:70, sep="") lm(output ~ myData[,features], data=myData) 

Is probably smarter as it doesn't matter where in amongst your data the columns are.

Might cause issues if there's row's removed for NA's though...