precision, recall and f-measure in R

Question

I haven't used R in a while, so maybe I'm just not used to it yet, but.. I have a table in R with two colums, the first one has predicted values (a value can be either 0 or 1), the second one has the actual values (also 0 or 1). I need to find recall, precision and f-measures, but cannot find a good function for it in R. (I also read about ROCR, but all I could do was creating some plots, but I really don't need plots, I need the numbers).

Is there any good functions for finding precision, recall and f-measure in R? Are there any different ways to do it?

Answer 1

measurePrecisionRecall <- function(actual_labels, predict){
  conMatrix = table(actual_labels, predict)
  precision <- conMatrix['0','0'] / ifelse(sum(conMatrix[,'0'])== 0, 1, sum(conMatrix[,'0']))
  recall <- conMatrix['0','0'] / ifelse(sum(conMatrix['0',])== 0, 1, sum(conMatrix['0',]))
  fmeasure <- 2 * precision * recall / ifelse(precision + recall == 0, 1, precision + recall)

  cat('precision:  ')
  cat(precision * 100)
  cat('%')
  cat('\n')

  cat('recall:     ')
  cat(recall * 100)
  cat('%')
  cat('\n')

  cat('f-measure:  ')
  cat(fmeasure * 100)
  cat('%')
  cat('\n')
}