[ANNOUNCE] AI::Categorize 0.06 -> CPAN

Hi,

I've just uploaded a new version of AI::Categorize to CPAN.  You'll
find the new version (0.06) at http://www.cpan.org/modules/by-module/AI/ 
as
soon as CPAN propogates the upload.

Changes in version 0.06:

  - Fixed a bug which resulted in incorrect probabilities in
    NaiveBayes categorize() calculations.

  - Threshold for Naive Bayes categorizer is now a settable parameter,
    letting you tune performance to balance precision and recall to
    suit your needs.  Default threshold is 0.3 (used to be fixed at 0.5).

  - Added the precision() and recall() methods, which are another set
    of measures of how good a categorizer is.

  - Wrote documentation for the VectorBased superclass - it was
    previously vestigial docs from the kNN module (oops).

  - No changes made to the kNN categorizer - however, the precision
    and recall scores below show that clearly some changes are needed.
    The main problem is the setting of thresholds, and I've done some
    work in this area that's already improved scores, but it's not
    ready yet.

  - Current scores on the drmath-1.00 corpus with features_kept => 0.1:
    ******************* Summary *********************************
    *        Name         miR   miP   miF1  error      time     *
    *   01-NaiveBayes:   0.226 0.280 0.239  0.018      79 sec 
*threshold=0.3
    *   01-NaiveBayes:   0.161 0.213 0.176  0.017      93 sec 
*threshold=0.5
    *          02-kNN:   0.650 0.109 0.178  0.105    2069 sec   *
    *************************************************************
    *  miR = micro-avg. recall     miP = micro-avg. precision   *
    *  miF = micro-avg. F1       error = micro-avg. error rate  *
    *************************************************************