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.IX Title "AI::Categorizer::Learner::Boolean 3"
.TH AI::Categorizer::Learner::Boolean 3 "2008-01-14" "perl v5.8.8" "User Contributed Perl Documentation"
.SH "NAME"
AI::Categorizer::Learner::Boolean \- Abstract class for boolean categorizers
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
.Vb 3
\& package AI::Categorizer::Learner::SomethingNew;
\& use AI::Categorizer::Learner::Boolean;
\& @ISA = qw(AI::Categorizer::Learner::Boolean);
.Ve
.PP
.Vb 5
\& sub create_boolean_model {
\&   my ($self, $positives, $negatives, $category) = @_;
\&   ...
\&   return $something_helpful;
\& }
.Ve
.PP
.Vb 5
\& sub get_boolean_score {
\&   my ($self, $document, $something_helpful) = @_;
\&   ...
\&   return $score;
\& }
.Ve
.SH "DESCRIPTION"
.IX Header "DESCRIPTION"
This is an abstract class which turns boolean categorizers
(categorizers based on algorithms that can just provide yes/no
categorization decisions for a single document and single category)
into multi-valued categorizers.  For instance, the decision tree
categorizer \f(CW\*(C`AI::Categorizer::Learner::DecisionTree\*(C'\fR maintains a
decision tree for each category, then uses it to decide whether a
certain document belongs to the given category.
.PP
Any class that inherits from this class should implement the following
methods:
.Sh "\fIcreate_boolean_model()\fP"
.IX Subsection "create_boolean_model()"
Used during training to create a category-specific model.  The type of
model you create is up to you \- it should be returned as a scalar.
Whatever you return will be available to you in the
\&\f(CW\*(C`get_boolean_score()\*(C'\fR method, so put any information you'll need
during categorization in this scalar.
.PP
In addition to \f(CW$self\fR, this method will be passed three arguments.
The first argument is a reference to an array of \fBpositive\fR examples,
i.e. documents that belong to the given category.  The next argument
is a reference to an array of \fBnegative\fR examples, i.e. documents
that do \fInot\fR belong to the given category.  The final argument is
the Category object for the given category.
.Sh "\fIget_boolean_score()\fP"
.IX Subsection "get_boolean_score()"
Used during categorization to assign a score for a single document
relative to a single category.  The score should be between 0 and 1,
with a score greater than 0.5 indicating membership in the category.
.PP
In addition to \f(CW$self\fR, this method will be passed two arguments.
The first argument is the document to be categorized.  The second
argument is the value returned by \f(CW\*(C`create_boolean_model()\*(C'\fR for this
category.
.SH "AUTHOR"
.IX Header "AUTHOR"
Ken Williams, <ken@mathforum.org>
.SH "SEE ALSO"
.IX Header "SEE ALSO"
AI::Categorizer