Data::CosineSimilarity - Compute the Cosine Similarity
$cs = Data::CosineSimilarity->new;
$cs->add( label1 => { feature1 => 3, feature2 => 1, feature3 => 10 } );
$cs->add( label2 => ... );
$cs->add( label3 => ... );
# computes the cosine similarity
my $r = $cs->similarity( 'label1', 'label2' );
# the result object
my $cosine = $r->cosine;
my $radian = $r->radian;
my $degree = $r->degree;
my ($label1, $label2) = $r->labels;
# computes all the cosine similarity between 'label1' and the others.
my @all = $cs->all_for_label('label1');
# computes all, and returns the best
my ($best_label, $r) = $cs->best_for_label('label2');
# computes all, and returns the worst
my ($worst_label, $r) = $cs->worst_for_label('label2');
Compute the cosine similarities between a set of vectors.
If all the feature vectors are normed then the computation of the cosine becomes just the dot product of the vectors. In this case, specify the option normed => 1, the performance will be greatly improved.
Antoine Imbert, <antoine.imbert at gmail.com>
This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself.
