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Multiple Output Regression with MLR (and NN)?

I wanted to create a Neural Network with multiple outputs (Multiple Output Regression - not classification) - as I never used mlr I wanted to try it and failed right away before coming to the Neural Network part, as I could not find a "task" for multiple output regression. The documentation is not helpful at all.

library(mlr)

a<-1:20
b<-a*3
d<-data.frame(a=a,b=b,T1=(a+b),T2=sin(a))

#make a regression task for target variables
task<- makeRegrTask(data = d, target = c("T1","T2"))

#Error in makeRegrTask(data = d, target = c("T1", "T2")) : 
#Assertion on 'target' failed: Must have length 1.

PS: I don't really have to use Neural Network, so I'm open for other suggestions with MLR as well as long as it's one model with multiple ouputs.

Solution

  • Multiple output regression isn't supported in mlr at the moment.