random forest - randomForest prediction issue in r -


i have been using randomforest package classification model categorical factors predictors. predict function fails when there new levels in test not in training. overcome that, have added missing levels follows:

mname<-get(model)  ( k in 1:ncol(dataframe)) {   col<-names(dataframe[k])   modellevels <- mname$forest$xlevels[[col]]   orig<-levels(dataframe[,k])   misses <-setdiff(modellevels,orig)   origordered <- orig[order(match(orig,modellevels))] # not sure if ordering matters   missordered <- misses[order(match(misses,modellevels))] # not sure if ordering matters   if(length(misses) > 0) { levels(dataframe[,k]) <- as.character(c(origordered,missordered)) } }  prediction <- data.frame(predict(mname,dataframe,type = "prob"))$x1

this prediction returns different values same input vector depending on size of dataframe provided prediction.

for example, if send dataframe 2 rows returns values of 0,0 whereas if pass bigger dataframe same 2 rows included throws prediction of 0.066667 same 2 rows?

could clarify reason behavior? unable share data here.


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