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.IX Title "AI::Categorizer::Learner 3"
.TH AI::Categorizer::Learner 3 "2008-01-14" "perl v5.8.8" "User Contributed Perl Documentation"
.SH "NAME"
AI::Categorizer::Learner \- Abstract Machine Learner Class
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
.Vb 1
\& use AI::Categorizer::Learner::NaiveBayes;  # Or other subclass
.Ve
.PP
.Vb 1
\& # Here $k is an AI::Categorizer::KnowledgeSet object
.Ve
.PP
.Vb 3
\& my $nb = new AI::Categorizer::Learner::NaiveBayes(...parameters...);
\& $nb->train(knowledge_set => $k);
\& $nb->save_state('filename');
.Ve
.PP
.Vb 1
\& ... time passes ...
.Ve
.PP
.Vb 7
\& $nb = AI::Categorizer::Learner::NaiveBayes->restore_state('filename');
\& my $c = new AI::Categorizer::Collection::Files( path => ... );
\& while (my $document = $c->next) {
\&   my $hypothesis = $nb->categorize($document);
\&   print "Best assigned category: ", $hypothesis->best_category, "\en";
\&   print "All assigned categories: ", join(', ', $hypothesis->categories), "\en";
\& }
.Ve
.SH "DESCRIPTION"
.IX Header "DESCRIPTION"
The \f(CW\*(C`AI::Categorizer::Learner\*(C'\fR class is an abstract class that will
never actually be directly used in your code.  Instead, you will use a
subclass like \f(CW\*(C`AI::Categorizer::Learner::NaiveBayes\*(C'\fR which implements
an actual machine learning algorithm.
.PP
The general description of the Learner interface is documented here.
.SH "METHODS"
.IX Header "METHODS"
.IP "\fInew()\fR" 4
.IX Item "new()"
Creates a new Learner and returns it.  Accepts the following
parameters:
.RS 4
.IP "knowledge_set" 4
.IX Item "knowledge_set"
A Knowledge Set that will be used by default during the \f(CW\*(C`train()\*(C'\fR
method.
.IP "verbose" 4
.IX Item "verbose"
If true, the Learner will display some diagnostic output while
training and categorizing documents.
.RE
.RS 4
.RE
.IP "\fItrain()\fR" 4
.IX Item "train()"
.PD 0
.ie n .IP "train(knowledge_set => $k)" 4
.el .IP "train(knowledge_set => \f(CW$k\fR)" 4
.IX Item "train(knowledge_set => $k)"
.PD
Trains the categorizer.  This prepares it for later use in
categorizing documents.  The \f(CW\*(C`knowledge_set\*(C'\fR parameter must provide
an object of the class \f(CW\*(C`AI::Categorizer::KnowledgeSet\*(C'\fR (or a subclass
thereof), populated with lots of documents and categories.  See
AI::Categorizer::KnowledgeSet for the details of how to create such
an object.  If you provided a \f(CW\*(C`knowledge_set\*(C'\fR parameter to \f(CW\*(C`new()\*(C'\fR,
specifying one here will override it.
.IP "categorize($document)" 4
.IX Item "categorize($document)"
Returns an \f(CW\*(C`AI::Categorizer::Hypothesis\*(C'\fR object representing the
categorizer's \*(L"best guess\*(R" about which categories the given document
should be assigned to.  See AI::Categorizer::Hypothesis for more
details on how to use this object.
.ie n .IP "categorize_collection(collection => $collection)" 4
.el .IP "categorize_collection(collection => \f(CW$collection\fR)" 4
.IX Item "categorize_collection(collection => $collection)"
Categorizes every document in a collection and returns an Experiment
object representing the results.  Note that the Experiment does not
contain knowledge of the assigned categories for every document, only
a statistical summary of the results.
.IP "\fIknowledge_set()\fR" 4
.IX Item "knowledge_set()"
Gets/sets the internal \f(CW\*(C`knowledge_set\*(C'\fR member.  Note that since the
knowledge set may be enormous, some Learners may throw away their
knowledge set after training or after restoring state from a file.
.IP "$learner\->save_state($path)" 4
.IX Item "$learner->save_state($path)"
Saves the Learner for later use.  This method is inherited from
\&\f(CW\*(C`AI::Categorizer::Storable\*(C'\fR.
.IP "$class\->restore_state($path)" 4
.IX Item "$class->restore_state($path)"
Returns a Learner saved in a file with \f(CW\*(C`save_state()\*(C'\fR.  This method
is inherited from \f(CW\*(C`AI::Categorizer::Storable\*(C'\fR.
.SH "AUTHOR"
.IX Header "AUTHOR"
Ken Williams, ken@mathforum.org
.SH "COPYRIGHT"
.IX Header "COPYRIGHT"
Copyright 2000\-2003 Ken Williams.  All rights reserved.
.PP
This library is free software; you can redistribute it and/or
modify it under the same terms as Perl itself.
.SH "SEE ALSO"
.IX Header "SEE ALSO"
\&\fIAI::Categorizer\fR\|(3)