R/bootrf.r

In shipunov: Miscellaneous Functions from Alexey Shipunov

BootRF <- function(data, classes, sub="none", nsam=4, nboot=1000, misclass=TRUE, ...) {
 PRED <- matrix(character(0), nrow=nrow(data), ncol=nboot)
 TBL <- table(classes, classes)
 TBL[TBL > 0] <- 0
 for(b in 1:nboot) {
  cat(".")
  if (length(sub) == 1 && sub == "none") sub <- !logical(nrow(data))
  data.sub <- data[sub, ]
  classes.sub <- classes[sub]
  sel <- ave(seq_len(nrow(data.sub)), classes.sub, FUN=function(.x) sample.int(length(.x))) <= nsam
  train <- data.sub[sel, ]
  classes.train <- classes.sub[sel]
  model <- randomForest::randomForest(classes.train ~ ., data=train, ...)
  pred <- predict(model, data)
  if (misclass) TBL <- TBL + table(pred, classes)
  PRED[, b] <- as.character(pred)
 }
 cat("\n")
 if(misclass){
  cat("\n")
  TBLb <- round(TBL/nboot)
  sum <- colSums(TBLb)
  dia <- diag(TBLb)
  msc <- (sum - dia)/sum * 100
  m.m <- mean(msc)
  cat("Classification table:", "\n")
  print(TBLb)
  cat("Misclassification errors:", "\n")
  print(round(msc, 1))
  cat("Mean misclassification error: ", round(m.m, 1), "%", "\n", sep="")
 }
invisible(PRED)
}