pcut algorithms

pcut.r

library(ggplot2)
library(utiml)


print("Hello, world!")

pcut_thresholdk <- function (prediction, ratio, probability = FALSE) {
  UseMethod("pcut_thresholdk")
}

pcut_thresholdk.default <- function (prediction, ratio, probability = FALSE) {
print("line")

  n <- nrow(prediction)
print(n)
print(ratio)

  num.elem <- ceiling(ratio * n)
print(num.elem)
print(ncol(prediction))

  if (length(num.elem) == 1) {
    print("len 1")

    num.elem <- rep(num.elem, ncol(prediction))
print(num.elem)

    names(num.elem) <- colnames(prediction)
print(names(num.elem))
  }
  else if (length(num.elem) != ncol(prediction)) {
    stop(paste("The number of elements values must be a single value or the",
               "same number of labels"))
  }
  else if (is.null(names(num.elem))) {
    names(num.elem) <- colnames(prediction)
  }

  indexes <- utiml_rename(seq(ncol(prediction)), colnames(prediction))
print(indexes)

  result <- do.call(cbind, lapply(indexes, function (ncol) {
    values <- c(rep(1, num.elem[ncol]), rep(0, n - num.elem[ncol]))
print("values")
print(values)
print(prediction[, ncol])

    prediction[order(prediction[, ncol], decreasing=TRUE), ncol] <- values
print("ncol")
print(ncol)
print("predict and order")
print(prediction[, ncol])
print(order(prediction[, ncol]))
print("result")
print(prediction[order(prediction[, ncol], decreasing=TRUE), ncol])
print(prediction[, ncol])


    prediction[, ncol]
  }))

  multilabel_prediction(result, prediction, probability)
}

pcut_thresholdk.mlresult <- function (prediction, ratio, probability = FALSE) {
  pcut_thresholdk.default(as.probability(prediction), ratio, probability)
}
prediction <- matrix(runif(16), ncol = 4)
prediction
pcut_thresholdk(prediction, .45)