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