view release on metacpan or  search on metacpan

lib/Algorithm/AM.pm  view on Meta::CPAN

=back

=head2 C<training_set>

Returns (but will not set) the dataset used for training. This is
an instance of L<Algorithm::AM::DataSet>.

=head2 C<exclude_nulls>

Get/set a boolean value indicating whether features with null
values in the test item should be ignored. If false, they will be
treated as having a specific value representing null.
Defaults to true.

=head2 C<exclude_given>

Get/set a boolean value indicating whether the test item should be
removed from the training set if it is found there during
classification. Defaults to true.

=head2 C<linear>

Get/set a boolean value indicating whether the analogical set should
be computed using I<occurrences> (linearly) or I<pointers>
(quadratically). To understand what this means, you should read the
L<algorithm|Algorithm::AM::algorithm> page. A false value indicates
quadratic counting. Defaults to false.

=head2 C<classify>

  $am->classify(new_item(features => ['a','b','c']));

Using the analogical modeling algorithm, this method classifies
the input test item and returns a L<Result|Algorithm::AM::Result>
object.

L<Log::Any> is used for logging. The full classification configuration
is logged at the info level. A notice is printed at the warning
level if no training items can be compared with the test item,
preventing any classification.

=head1 HISTORY

Initially, Analogical Modeling was implemented as a Pascal program.
Subsequently, it was ported to Perl, with substantial improvements
made in 2000. In 2001, the core of the algorithm was rewritten in C,
while the parsing, printing, and statistical routines remained in C;
this was accomplished by embedding a Perl interpreter into the C code.

In 2004, the algorithm was again rewritten, this time in order to
handle more features and large data sets. The algorithm breaks the
supracontextual lattice into the direct product of four smaller ones,
which the algorithm manipulates individually before recombining.
These lattices can be manipulated in parallel when using the right
hardware, and so the module was named C<AM::Parallel>. This
implementation was written with the core lattice-filling algorithm in
XS, and hooks were provided to help the user create custom reports
and control classification dynamically.

The present version has been renamed to C<Algorithm::AM>, which seemed
a better fit for CPAN. While the XS has largely remained intact, the
Perl code has been completely reorganized and updated to be both more
"modern" and modular. Most of the functionality of C<AM::Parallel>
remains.

=head1 SEE ALSO

The <home page|http://humanities.byu.edu/am/> for Analogical Modeling
includes information about current research and publications, as well as
sample data sets.

The L<Wikipedia article|http://en.wikipedia.org/wiki/Analogical_modeling>
has details and even illustrations on analogical modeling.

=for :stopwords cpan testmatrix url bugtracker rt cpants kwalitee diff irc mailto metadata placeholders metacpan

=head1 SUPPORT

=head2 Bugs / Feature Requests

Please report any bugs or feature requests through the issue tracker
at L<https://github.com/garfieldnate/Algorithm-AM/issues>.
You will be notified automatically of any progress on your issue.

=head2 Source Code

This is open source software.  The code repository is available for
public review and contribution under the terms of the license.

L<https://github.com/garfieldnate/Algorithm-AM>

  git clone https://github.com/garfieldnate/Algorithm-AM.git

=head1 AUTHOR

Theron Stanford <shixilun@yahoo.com>, Nathan Glenn <garfieldnate@gmail.com>

=head1 CONTRIBUTORS

=for stopwords Nathan Glenn Nick Logan Richard Leach

=over 4

=item *

Nathan Glenn <nathan-gary.glenn@trivago.com>

=item *

Nick Logan <nlogan@gmail.com>

=item *

Richard Leach <richardleach@users.noreply.github.com>

=back

=head1 COPYRIGHT AND LICENSE

This software is copyright (c) 2021 by Royal Skousen.