Description Usage Arguments Examples
View source: R/varsel_regression_rf.R
Similar approach to varSelRF, but for regresssion. Use full model to rank variables based on either imporatance = TRUE. It then steps through that sorted variable list with most important first and runs RF, store variables and Note: this sorts on Gini, by default. importance = TRUE ensures
1 | varsel_regression_rf(y, x, prog = F, ...)
|
y |
response a vector |
x |
predictors a data.frame |
... |
options to pass to randomForest |
1 2 3 4 5 6 | data(LakeTrophicModelling)
predictors_all <- predictors_all[predictors_all!="DATE_COL"]
all_dat <- data.frame(ltmData[predictors_all],LogCHLA=log10(ltmData$CHLA))
all_dat <- all_dat[complete.cases(all_dat),]
x<-varsel_regression_rf(all_dat$LogCHLA,all_dat[,names(all_dat)!="LogCHLA"],
ntree=100,prog=T, importance = TRUE)
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