R/createFolds_xllim.R

In epertham/xLLiM: High Dimensional Locally-Linear Mapping

createFolds_xllim <- function (y, k = 10, list = TRUE, returnTrain = FALSE) 
{# adapted from the createFolds function of caret package
  if (class(y)[1] == "Surv") 
    y <- y[, "time"]
  if (is.numeric(y)) {
    cuts <- floor(length(y)/k)
    if (cuts < 2) 
      cuts <- 2
    if (cuts > 5) 
      cuts <- 5
    breaks <- unique(quantile(y, probs = seq(0, 1, length = cuts)))
    y <- cut(y, breaks, include.lowest = TRUE)
  }
  if (k < length(y)) {
    y <- factor(as.character(y))
    numInClass <- table(y)
    foldVector <- vector(mode = "integer", length(y))
    for (i in 1:length(numInClass)) {
      min_reps <- numInClass[i]%/%k
      if (min_reps > 0) {
        spares <- numInClass[i]%%k
        seqVector <- rep(1:k, min_reps)
        if (spares > 0) 
          seqVector <- c(seqVector, sample(1:k, spares))
        foldVector[which(y == names(numInClass)[i])] <- sample(seqVector)
      }
      else {
        foldVector[which(y == names(numInClass)[i])] <- sample(1:k,size = numInClass[i])
      }
    }
  }
  else foldVector <- seq(along = y)
  if (list) {
    out <- split(seq(along = y), foldVector)
    names(out) <- paste("Fold", gsub(" ", "0", format(seq(along = out))),sep = "")
    if (returnTrain) 
      out <- lapply(out, function(data, y) y[-data], y = seq(along = y))
  }
  else out <- foldVector
  return(out)
}