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lib/AI/Categorizer/Experiment.pm  view on Meta::CPAN

C<Statistics::Contingency>.  Please see the documentation of
C<Statistics::Contingency> for a description of its interface.  All of
its methods are available here, with the following additions:

=over 4

=item new( categories => \%categories )

=item new( categories => \@categories, verbose => 1, sig_figs => 2 )

Returns a new Experiment object.  A required C<categories> parameter
specifies the names of all categories in the data set.  The category
names may be specified either the keys in a reference to a hash, or as
the entries in a reference to an array.

The C<new()> method accepts a C<verbose> parameter which
will cause some status/debugging information to be printed to
C<STDOUT> when C<verbose> is set to a true value.

A C<sig_figs> indicates the number of significant figures that should
be used when showing the results in the C<results_table()> method.  It

lib/AI/Categorizer/Hypothesis.pm  view on Meta::CPAN

are returned by the Learner's C<categorize()> method.  However, if you
wish to create a Hypothesis directly (maybe passing it some fake data
for testing purposes) you may do so using the C<new()> method.

The following parameters are accepted when creating a new Hypothesis:

=over 4

=item all_categories

A required parameter which gives the set of all categories that could
possibly be assigned to.  The categories should be specified as a
reference to an array of category names (as strings).

=item scores

A hash reference indicating the assignment score for each category.
Any score higher than the C<threshold> will be considered to be
assigned.

=item threshold