[R] Recursive feature elimination keeping the weights constant

Dear All, I am trying to build a model by doing recursive elimination of weights one by one. This is the example matrix ID 885038 885039 885040 885041 885042 885043 Label weights 0.000236 0.004591 0.00017 0.018113 0.000238 0.006537 N/A 1267359 2 0 0 0 0 1 1 1295720 0 0 0 0 0 1 1 1295721

Re: [R] Recursive Feature Elimination with SVM

FALSE),]) a <- as.matrix(w2[which(w2 == max(w2)),]) #to get the rows with minimum values row.names(a) -> remove training<- data[,setdiff(colnames(data),remove)] } On Wed, Jan 2, 2019 at 11:18 AM David Winsemius wrote: > > On 1/1/19 5:31 PM, Priyanka Purkayastha w

Re: [R] Recursive Feature Elimination with SVM

Thankyou David.. I tried the same, I gave x as the data matrix and y as the class label. But it returned an empty "featureRankedList". I get no output when I try the code. On Tue, 1 Jan 2019 at 11:42 PM, David Winsemius wrote: > > On 1/1/19 4:40 AM, Priyanka Purkayastha wro

[R] Recursive Feature Elimination with SVM

I have a dataset (data) with 700 rows and 7000 columns. I am trying to do recursive feature selection with the SVM model. A quick google search helped me get a code for a recursive search with SVM. However, I am unable to understand the first part of the code, How do I introduce my dataset in the c