结合Amelia估算数据的多个随机森林模型

Question

I just created 40 imputed data sets using the Amelia package, and they are stored in a.out.

I then used the lapply function to create randomforest models on the data sets:

rf.amelia.out = lapply(a.out$imputations, function(i) randomForest(y + x1+x2, data = i) )

Now I would like to combine these models to make a prediction on a bunch a.test.out, which is a list of amelia imputed data testing data.

I can't figure out how to combine these random forest models. I've tried randomforest combine function like combine(rf.amelia.out) but that didn't work. The problem is that rf.amelia.out is not a model object, but neither is rf.amelia.out[1] .

I also tried to use zelig to automatically combine multiple models:

rf.z.out = zelig(y~x1+x2, data = a.out, model = "rf")

But I don't think zelig supports random forest models.

How do I access and combine the multiple random forest models so that I can make one prediction?

Answer 1

Since rf.amelia.out is already a list, the combine function in randomForest loses its methods when it tries to convert it to a list again. I recommend one of two fixes:

1. Change the combine function and then use the modified version:

   body(combine)[[4]] <- substitute(rflist <- (...))

   rf.all <- combine(rf.amelia.out)

2. Or use:

   combine(rf.amelia.out[[1]].rf.amelia.out[[2]],...)

I think the first way is easier (and much less manual).