AI-DecisionTree
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0.03 Mon Sep 2 11:41:18 AEST 2002
- Added a 'prune' parameter to new(), which controls whether the tree
will be pruned after training. This is usually a good idea, so the
default is to prune. Currently we prune using a simple
minimum-description-length criterion.
- Training instances are now represented using a C struct rather than
a Perl hash. This can dramatically reduce memory usage, though it
doesn't have much effect on speed. Note that Inline.pm is now
required.
- The list of instances is now deleted after training, since it's no
longer needed.
- Small speedup to the train() method, achieved by less copying of data.
- If get_result() is called in a list context, it now returns a list
containing the assigned result, a "confidence" score (tentative,
subject to change), and the tree depth of the leaf this instance
ended up at.
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t/author-critic.t view on Meta::CPAN
}
use strict;
use warnings;
use Test::More;
use English qw(-no_match_vars);
eval "use Test::Perl::Critic";
plan skip_all => 'Test::Perl::Critic required to criticise code' if $@;
Test::Perl::Critic->import( -profile => "perlcritic.rc" ) if -e "perlcritic.rc";
all_critic_ok();
( run in 0.555 second using v1.01-cache-2.11-cpan-0a6323c29d9 )