/ 
AI-Categorizer-0.09
River stage one • 1 direct dependent • 1 total dependent
/ AI::Categorizer::FeatureSelector::ChiSquare

NAME

AI::Categorizer::FeatureSelector::ChiSquare - ChiSquare Feature Selection class

SYNOPSIS

# the recommended way to use this class is to let the KnowledgeSet
# instanciate it

use AI::Categorizer::KnowledgeSetSMART;
my $ksetCHI = new AI::Categorizer::KnowledgeSetSMART(
  tfidf_notation =>'Categorizer',
  feature_selection=>'chi_square', ...other parameters...); 

# however it is also possible to pass an instance to the KnowledgeSet

use AI::Categorizer::KnowledgeSet;
use AI::Categorizer::FeatureSelector::ChiSquare;
my $ksetCHI = new AI::Categorizer::KnowledgeSet(
  feature_selector => new ChiSquare(features_kept=>2000,verbose=>1),
  ...other parameters...
  );

DESCRIPTION

Feature selection with the ChiSquare function.

Chi-Square(t,ci) = (N.(AD-CB)^2)
                  -----------------------
                  (A+C).(B+D).(A+B).(C+D)

where t = term ci = category i N = number of documents in the collection A = number of times where t and c co-occur B = " " " t occurs without c C = " " " c occurs without t D = " " " neither c nor t occur

for more details, see : Yiming Yang, Jan O. Pedersen, A Comparative Study on Feature Selection in Text Categorization, in Proceedings of ICML-97, 14th International Conference on Machine Learning, 1997. (available on citeseer.nj.nec.com)

METHODS

AUTHOR

Francois Paradis, paradifr@iro.umontreal.ca with inspiration from Ken Williams AI::Categorizer code