Zbigniew Łukasiak > AI-NaiveBayes-0.02 > AI::NaiveBayes::Learner

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Module Version: 0.02   Source  

NAME ^

AI::NaiveBayes::Learner - Build AI::NaiveBayes classifier from a set of training examples.

VERSION ^

version 0.02

SYNOPSIS ^

    my $learner = AI::NaiveBayes::Learner->new(features_kept => 0.5);
    $learner->add_example(
        { 
            attributes => { sheep => 1, very => 1, valuable => 1, farming => 1 },
            labels => ['farming'] 
        },
    );

    my $classifier = $learner->classifier;

DESCRIPTION ^

This is a trainer of AI::NaiveBayes classifiers. It saves information passed by the add_example method from training data into internal structures and then constructs a classifier when the classifier method is called.

ATTRIBUTES ^

features_kept

Indicates how many features should remain after calculating probabilities. By default all of them will be kept. For features_kept > 1, features_kept of features will be preserved. For values lower than 1, a specified fraction of features will be kept (e.g. top 20% of features for features_kept = 0.2).

The rest of the attributes is for class' internal usage, and thus not documented.

classifier_class

The class of the classifier to be created. By default it is AI::NaiveBayes

METHODS ^

add_example( HASHREF )

Saves the information from a training example into internal data structures. The parameter should be of the form of { feature1 => weight1, feature2 => weight2, ... }

classifier()
    Creates an AI::NaiveBayes classifier based on the data accumulated before.

UTILITY SUBS ^

add_hash

BASED ON ^

Much of the code and description is from Algorithm::NaiveBayes.

AUTHORS ^

COPYRIGHT AND LICENSE ^

This software is copyright (c) 2012 by Opera Software ASA.

This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.

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