问题
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.
回答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).
回答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...
来源：https://stackoverflow.com/questions/5774813/short-formula-call-for-many-variables-when-building-a-model