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lib/AI/NaiveBayes/Classification.pm  view on Meta::CPAN

=over 4

=item C<best_category()>

Returns a string being a label that suits given document the best.

=item C<find_predictors()>

This method returns the C<best_category()>, as well as the list of all the predictors
along with their influence on the best category selected. So the second value
returned is a list of array references, where each one contains a string being a
single feature and a number describing its influence on the result. So the
second part of the result may look like this:

    (
        [ 'activities',  1.2511540632952 ],
        [ 'over',       -1.0269523272981 ],
        [ 'provide',     0.8280157033269 ],
        [ 'natural',     0.7361042359385 ],
        [ 'against',    -0.6923354975173 ],
    )

=back

lib/AI/NaiveBayes/Learner.pm  view on Meta::CPAN

            my @top = @features[0..$limit-1];
            my %kept = map { $_ => $old{$_} } @top;
            $model->{probs}{$label} = \%kept;
        }
    }
    my $classifier_class = $self->classifier_class;
    return $classifier_class->new( model => $model );
}

sub add_hash {
    my ($first, $second) = @_;
    $first //= {};
    foreach my $k (keys %$second) {
        $first->{$k} //= 0;
        $first->{$k} += $second->{$k};
    }
}

__PACKAGE__->meta->make_immutable;

1;

=pod

=encoding UTF-8