AI-NaiveBayes
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Revision history for AI::NaiveBayes
0.04 2017-01-20
Some doc fixes
Moved do my personal github repo
0.03
Synopsis example fixed
0.02
added 'train' class method for quick start
0.01
initial release
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__END__
# ABSTRACT: A Bayesian classifier
=encoding utf8
=head1 SYNOPSIS
# AI::NaiveBayes objects are created by AI::NaiveBayes::Learner
# but for quick start you can use the 'train' class method
# that is a shortcut using default AI::NaiveBayes::Learner settings
my $classifier = AI::NaiveBayes->train(
{
attributes => {
sheep => 1, very => 1, valuable => 1, farming => 1
},
labels => ['farming']
},
{
my $best_category = $result->best_category;
=head1 DESCRIPTION
This module implements the classic "Naive Bayes" machine learning
algorithm. This is a low level class that accepts only pre-computed feature-vectors
as input, see L<AI::Classifier::Text> for a text classifier that uses
this class.
Creation of C<AI::NaiveBayes> classifier object out of training
data is done by L<AI::NaiveBayes::Learner>. For quick start
you can use the limited C<train> class method that trains the
classifier in a default way.
The classifier object is immutable.
It is a well-studied probabilistic algorithm often used in
automatic text categorization. Compared to other algorithms (kNN,
SVM, Decision Trees), it's pretty fast and reasonably competitive in
the quality of its results.
lib/AI/NaiveBayes.pm view on Meta::CPAN
AI::NaiveBayes - A Bayesian classifier
=head1 VERSION
version 0.04
=head1 SYNOPSIS
# AI::NaiveBayes objects are created by AI::NaiveBayes::Learner
# but for quick start you can use the 'train' class method
# that is a shortcut using default AI::NaiveBayes::Learner settings
my $classifier = AI::NaiveBayes->train(
{
attributes => {
sheep => 1, very => 1, valuable => 1, farming => 1
},
labels => ['farming']
},
{
lib/AI/NaiveBayes.pm view on Meta::CPAN
my $best_category = $result->best_category;
=head1 DESCRIPTION
This module implements the classic "Naive Bayes" machine learning
algorithm. This is a low level class that accepts only pre-computed feature-vectors
as input, see L<AI::Classifier::Text> for a text classifier that uses
this class.
Creation of C<AI::NaiveBayes> classifier object out of training
data is done by L<AI::NaiveBayes::Learner>. For quick start
you can use the limited C<train> class method that trains the
classifier in a default way.
The classifier object is immutable.
It is a well-studied probabilistic algorithm often used in
automatic text categorization. Compared to other algorithms (kNN,
SVM, Decision Trees), it's pretty fast and reasonably competitive in
the quality of its results.
( run in 0.244 second using v1.01-cache-2.11-cpan-0d8aa00de5b )