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Revision history for Perl extension AI::DecisionTree.
0.11 - Fri Mar 2 21:26:51 CST 2012
- Fixed typo in docs - 'leaf_color' should be 'leaf_colors'. [spotted
by Julio Fraire]
- Silence a couple of Perl::Critic warnings
- Convert to Dist::Zilla
0.09 - Sat Jul 26 23:09:44 2008
- Make a new release so that a META.yml file is generated. [Suggested
by Alexandr Ciornii]
- as_graphviz(%args) wasn't passing %args through properly to the
GraphViz->new() method. Fixed. [Ian Knopke]
- get_result() can now take a callback subroutine, rather than just a
hash reference, to check the attributes of the given instance.
This allows lazy instance checking.
0.08 Mon Jul 7 18:01:16 CDT 2003
- Added a 'leaf_color' parameter for making GraphViz objects more
colorful.
0.07 Fri Jun 6 10:37:51 CDT 2003
- Created tests for the set_results() and copy_instances() methods.
- Added documentation for as_graphviz() and increased the information
contained in the GraphViz object.
- Added the ability to limit the absolute depth of the tree when
training.
0.06 Wed Sep 18 13:59:24 EST 2002
- Fixed an XS memory leak that was afflicting all training instances.
Added tests to make sure leak stays plugged.
- Added the 'purge' and 'verbose' parameters to new().
- add_instance() now accepts a 'name' parameter.
- Users can now control whether training instances are purged after
training, using the 'purge' parameter to new() and/or the
do_purge() method.
- Added the set_results() and copy_instances() methods, which let you
re-use training instances from one tree to another.
- Added the instances() and purge() accessor methods.
0.05 Thu Sep 12 01:22:34 AEST 2002
- Fixed a concurrency problem that occurred when making more than one
decision tree. All tree data is now stored as member data, not
class data.
- DecisionTree.pm is now pure-perl again (though Instance.pm still
has an XS component).
- Fixed a one-off bug in the Instance.xs code that could create
garbage data.
- Handles "sparse" data better. Sparse data means that every
attribute doesn't have to be defined for every training/test
instance. This can now be a meaningful property - the absence of a
value is currently equivalent to a special "<undef>" value.
- Don't trigger warnings when undefined attribute values are
encountered (as happens with sparse data).
- Added documentation for the 'prune' parameter to new()
- More consistent with memory allocation in Instance.xs - uses the
perl memory macros/functions from `perldoc perlclib` instead of raw
malloc/realloc/free.
- Catches possible infinite loop situations when growing the tree
(which shouldn't usually happen, but other mistakes can cause it)
- The Instance class now has a numeric-only interface, without string
translation. String translation is done in the main DecisionTree
class. This isn't really a user-visible change.
0.04 Wed Sep 4 19:52:23 AEST 2002
- Now uses regular XS instead of Inline for the C code parts. [patch
by Matt Sergeant]
- Converted the inner loop of the best_attr() method to C code,
because it was spending a lot of time in accessor methods for the C
structures it was using. Don't worry, I'm not going C-crazy. I
won't be making many (any?) more of these kinds of changes, but
these ones were probably necessary.
- Removed a bit of debugging code that I left in for 0.03.
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.
- Internally, each node in the tree now contains information about
how many training examples contributed to training this node, and
what the distribution of their classes was.
- Added an as_graphviz() method, which will help visualize trees.
They're not terribly pretty graphviz objects yet, but they're
visual.
0.02 Sat Aug 10, 2002 21:02 AEST
- Added support for noisy data, currently by picking the best (most
common) result when noise is encountered. See the 'noise_mode'
parameter to new().
- Added the rule_tree() method, which returns a data structure
representing the tree. [James Smith]
- Significantly sped up the train() method, especially for large data
sets.
- The get_result() method is no longer implemented recursively, which
simplifies it and speeds it up.
- Reformatted the documentation and added a TO DO section.
- Documented the nodes() method.
0.01 Sat Jun 8 12:45:03 2002
- original version; created by h2xs 1.21 with options
-XA -n AI::DecisionTree
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