[Caml-list] [ANN] first release of cpm: the Classification Performance Metrics library

[Francois BERENGER <berenger@bioreg.kyushu-u.ac.jp>]

O Caml riders,

It is my pleasure to announce the first release of cpm.

cpm allows to compute various classification performance metrics, like:
- area under the ROC curve (AUC)
- BEDROC (Bolzmann Enhanced Discrimination of the ROC curve)
- Power Metric (PM) at given threshold
- Enrichment Factor (EF) at given percentage

Here is an example use:
---
(* first, define your score_label module *)
module SL = struct
   type t = string * float * int * bool
   let get_score (_, s, _, _) = s
   let get_label (_, _, _, l) = l
end

(* second, instantiate the ROC functor for your score_label module *)
module ROC = MakeROC.Make (SL)

(* third, call any classification performance metric you need *)
[...]
let auc = ROC.auc scores in
[...]
---

The score is the output of your predictor.
For a true positive, the label must be 1.
For a true negative, the label must be 0.
Your predictor is supposed to give high scores to true positives
and low scores to true negatives.

The code is here:
https://github.com/UnixJunkie/cpmlib

The library should be available shortly in opam under the name cpm.

For those who like to read, here are some interesting reads on related 
subjects:
- https://jcheminf.springeropen.com/articles/10.1186/s13321-016-0189-4
- 
https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btq140
- http://pubs.acs.org/doi/abs/10.1021/ci600426e

Have fun classifying,
F.