[R] cross validation in random forest using rfcv functin
Elahe chalabi
chalabi.elahe at yahoo.de
Wed Aug 23 14:38:42 CEST 2017
Hi all,
I would like to do cross validation in random forest using rfcv function. As the documentation for this package says:
rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...)
however I don't know how to build trianx and trainy for my data set, and I could not understand the way trainx is built in the package documentation example for iris data set.
Here is my data set and I want to do cross validation to see accuracy in classifying Alzheimer and Control Group:
str(data)
'data.frame': 499 obs. of 606 variables:
$ Gender : int 0 0 0 0 0 1 1 1 1 1 ...
$ NumOfWords : num 157 111 163 176 100 124 201 100 76 101
$ NumofLivings : int 6 6 9 4 3 5 3 3 4 3 ...
$ NumofStopWords: num 77 45 87 91 46 64 104 37 32 41 ...
.
.
$ Group : Factor w/ 2 levels "Alzheimer","Control","Control"..:
So basically trainy should be data$Group but how about trainx? Could anyone help me in this?
Thanks for any help!
Elahe
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