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AI-Categorize-0.05.tar.gz
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The changes are:
---------------------------------------------------------------
- Made lots of improvements to the NaiveBayes categorizer. It was
so bad as to be essentially useless before. Now it is scoring better
in F1, accuracy, and running time than the kNN categorizer on my
standard test corpus. This improvement came from studying Tom
Mitchell's excellent book "Machine Learning".
01-NaiveBayes: F1=0.195 accuracy=0.981 time= 99 sec
02-kNN: F1=0.169 accuracy=0.889 time=1199 sec
- Increased the efficiency of the category map. Added boolean
is_in_category() and contains_document() methods.
- Fixed a bug in the AI::Categorize::Evaluate class in which
default arguments weren't being passed properly to the created
classes.
- Cleaned up the formatting of the AI::Categorize::Evaluate output,
and added the accuracy score.
- Fixed a small problem in kNN in which it was using k-1 similar
documents instead of k.
- Added an accuracy() and error() method to AI::Categorize.
Calculates the accuracy/error over all binary category membership
decisions. Has the same interface as the previous F1() method.
- Fixed the F1() method to return 1 (perfect score) when you
correctly assign zero categories.
- Added a cat_map() method to AI::Categorize class, which returns
the AI::Categorize::Map object so you can query this information.
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-Ken
