R/aum.R

In tdhock/aum: Area Under Minimum of False Positives and Negatives

aum <- structure(function
### Compute the Area Under Minimum of False Positives and False
### Negatives, and its directional derivatives.
(error.diff.df,
### data frame of error differences, typically computed via
### aum_diffs_binary or aum_diffs_penalty. There should be one row for
### each change in error functions. "example" column indicates example
### ID (int from 1 to N), "pred" column indicates predicted value
### where there is a change in the error function(s), "fp_diff" and
### "fn_diff" columns indicate differences in false positives and
### false negatives at that predicted value. Note that this
### representation assumes that each error function has fp=0 at
### pred=-Inf and fn=0 at pred=Inf.
  pred.vec
### numeric vector of N predicted values.
){
  L <- aum_sort_interface(error.diff.df, pred.vec)
  rownames(L[["derivative_mat"]]) <- names(pred.vec)
  L
### Named list of two items: aum is numeric scalar loss value,
### derivative_mat is N x 2 matrix of directional derivatives (first
### column is derivative from left, second column is derivative from
### right). If
}, ex=function(){

  (bin.diffs <- aum::aum_diffs_binary(c(0,1)))
  aum::aum(bin.diffs, c(-10,10))
  aum::aum(bin.diffs, c(0,0))
  aum::aum(bin.diffs, c(10,-10))

})