AI-Calibrate

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Changes  view on Meta::CPAN

      - Changes to ./t/AI-Calibrate-1.t to let it pass with almost-equal
        numbers.

1.4   Thu Aug 2 2012
      - Revised calibration algorithm based on bug
      - Updated tests in ./t
      - Added ./t/AI-Calibrate-KL.t using Kun Liu's dataset.
      - Added ./t/AI-Calibrate-pathologies.t to test for pathological cases.

1.3   Fri Nov 4
      - Removed dependency on Test::Deep, added explicit declaration of
        dependency on Test::More to Makefile.PL

1.2   Thu Nov 3
      - Fixed test ./t/AI-Calibrate-NB.t so that test wouldn't fail.  Used to
        call is_deeply, which was failing on slight differences between
        floating point numbers.  Now compares with a small tolerance.

1.1   Thu Feb 28 19:00:06 2008
      - Added new function print_mapping
      - Added new test file AI-Calibrate-NB.t which, if AI::NaiveBayes1 is
        present, trains a classifier and calibrates it.

META.json  view on Meta::CPAN

            "ExtUtils::MakeMaker" : 0
         }
      },
      "configure" : {
         "requires" : {
            "ExtUtils::MakeMaker" : 0
         }
      },
      "runtime" : {
         "requires" : {
            "Test::More" : 0
         }
      }
   },
   "release_status" : "stable",
   "version" : "1.5"
}

META.yml  view on Meta::CPAN

license: unknown
meta-spec:
  url: http://module-build.sourceforge.net/META-spec-v1.4.html
  version: 1.4
name: AI-Calibrate
no_index:
  directory:
    - t
    - inc
requires:
  Test::More: 0
version: 1.5

Makefile.PL  view on Meta::CPAN

use 5.008008;
use ExtUtils::MakeMaker;
# See lib/ExtUtils/MakeMaker.pm for details of how to influence
# the contents of the Makefile that is written.
WriteMakefile(
    NAME              => 'AI::Calibrate',
    VERSION_FROM      => 'lib/AI/Calibrate.pm', # finds $VERSION
    PREREQ_PM         => {Test::More => 0}, # e.g., Module::Name => 1.1
    ($] >= 5.005 ?     ## Add these new keywords supported since 5.005
      (ABSTRACT_FROM  => 'lib/AI/Calibrate.pm', # retrieve abstract from module
       AUTHOR         => 'Tom Fawcett <tfawcett@acm.org>') : ()),
);

t/AI-Calibrate-1.t  view on Meta::CPAN

#  -*- Mode: CPerl -*-
use strict;
# Before `make install' is performed this script should be runnable with
# `make test'. After `make install' it should work as `perl AI-Calibrate.t'

#########################

use Test::More tests => 34;
BEGIN { use_ok('AI::Calibrate', ':all') };

srand;

sub deeply_approx {
    # Like Test::More::is_deeply but uses approx() to compare elements.
    my( $got, $expected ) = @_;
    my $EPSILON = 1.0e-6;
    sub max {  $_[0] > $_[1] ? $_[0] : $_[1] }
    sub approx {
        my($x, $y) = @_;
        print("approx($x, $y)\n");
        if ($x == 0 and $y == 0) {
            return(1);
        } else {
            return(abs($x-$y) / max($x,$y) < $EPSILON);

t/AI-Calibrate-KL.t  view on Meta::CPAN

#  -*- Mode: CPerl -*-
use strict;
# Before `make install' is performed this script should be runnable with
# `make test'. After `make install' it should work as `perl AI-Calibrate.t'

#########################

use Test::More tests => 4;
BEGIN { use_ok('AI::Calibrate', ':all') };

sub trim($) {
    my $string = shift;
    $string =~ s/^\s+//;
    $string =~ s/\s+$//;
    return $string;
}

#  These points are from Kun Liu

t/AI-Calibrate-NB.t  view on Meta::CPAN

#  -*- Mode: CPerl -*-
use English;
use strict;
# Before `make install' is performed this script should be runnable with
# `make test'. After `make install' it should work as `perl AI-Calibrate.t'

use Test::More;

eval("use AI::NaiveBayes1");
if ($EVAL_ERROR) {
    plan skip_all => 'AI::NaiveBayes1 does not seem to be present';
} else {
    plan tests => 2;
}

use_ok('AI::Calibrate', ':all');

t/AI-Calibrate-pathologies.t  view on Meta::CPAN

#  -*- Mode: CPerl -*-
use strict;
# Before `make install' is performed this script should be runnable with
# `make test'. After `make install' it should work as `perl AI-Calibrate.t'

use Test::More tests => 6;
BEGIN { use_ok('AI::Calibrate', ':all') };

my $points0 = [ ];


use Data::Dumper;

is_deeply( calibrate($points0), [], "empty point set");

my $points1 = [

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