1:- module( mlu, [
    2                    % k_fold_learn/5,
    3                    k_fold_pairwise_comparisons/6,
    4                    k_fold_pairwise_predictions/6,
    5                    k_fold_segments/4,
    6                    mlu_sample/4, mlu_sample/5,
    7                    mlu_frequency_plot/2,
    8                    mlu_errors/0,
    9                    mlu_version/2
   10    ] ).   11
   12:- use_module( library(lists) ).   13:- use_module( library(lib) ).   14
   15:- lib(source(mlu),homonyms(true)).   16
   17:- lib(os_lib).   18:- lib(debug_call).   19:- lib(pack_errors).   20
   21:- lib(stoics_lib:at_con/3).   22:- lib(stoics_lib:arity/3).   23:- lib(stoics_lib:holds/2).   24
   25:- lib(k_fold_learn/5).   26:- lib(k_fold_pairwise_comparisons/6).   27:- lib(k_fold_pairwise_predictions/6).   28:- lib(k_fold_segments/4).   29:- lib(mlu_errors/0).   30:- lib(mlu_sample/4).   31:- lib(mlu_frequency_plot/2).   32:- lib(end(mlu)).

Machine learning utilities

A menagerie of machine learning utilities.

Currently implements k_fold learning and k_fold comparative performance plots via Real.

It is likely that bootstrapping will be added soon and also a couple of additional types of comparative plots.

Pack info

author
- nicos angelopoulos
version
- 0.1 2016/3/5
- 0.2 2017/3/11
- 0.3 2021/12/31
- 0.4 2022/1/2
- 0.5 2022/12/29
See also
- http://stoics.org.uk/~nicos/sware/mlu
- http://stoics.org.uk/~nicos/sware/mlu/doc/html/mlu.html
- pack(mlu/examples/stoic.pl)

*/




 mlu_version(-Version, -Date)
Current version and release date for the library.


?- mlu_version( V, D ).
V = 0:5:0,
D = date(2022, 12, 29).




*/


   66mlu_version( 0:5:0, date(2022,12,29) )