search for: data_imput

...sample3=sample(x,70) sample5=sample(x,70) ##########replace by missing values######### data_missing=data data_missing[sample1,1]=NA data_missing[sample3,3]=NA data_missing[sample5,5]=NA summary(data_missing) is.factor(data_missing$Cl.thickness)# OK ########imputation by random forest######## data_imputed <- rfImpute(Class ~ .,data_missing,iter=5,ntree=1000) is.factor(data_imputed$Cl.thickness)# Not OK And as you can see, rfImpute change the type of one explanatory variable. Before imputation, it was a factor. After it becomes a quantitative variable. So I don't understand what it happ...