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  1. FromDate
  2. Grant Ingersoll2009-06-16 17:35
  3. Shashikant Kore2009-06-16 23:43
  4. Ted Dunning2009-06-17 02:51
  5. Grant Ingersoll2009-06-17 09:14
  6. Grant Ingersoll2009-06-17 09:32
  7. Shashikant Kore2009-06-18 06:17
  8. Grant Ingersoll2009-07-14 09:41
  9. Ted Dunning2009-07-27 21:42
  10. Benson Margulies2009-07-27 21:51
  11. Ted Dunning2009-07-28 00:48
  12. Grant Ingersoll2009-07-28 06:55
  13. Benson Margulies2009-07-28 14:49
  14. Ted Dunning2009-07-28 16:36
  15. Grant Ingersoll2009-08-18 09:55
  16. Grant Ingersoll2009-08-18 10:32
  17. Benjamin Dageroth2009-08-18 11:37
  18. Ted Dunning2009-08-18 13:04
  19. Grant Ingersoll2009-08-18 13:49
  20. Jack Tanner2009-08-18 17:40
  21. Grant Ingersoll2010-01-09 12:18
  22. Grant Ingersoll2010-01-09 13:57
  23. Ted Dunning2010-01-09 15:31
  24. Ted Dunning2010-01-09 15:32

[mahout-user] Validating clustering output

Subject:
Re: Validating clustering output
From:
Grant Ingersoll <gsingers@...>
Date:
2010-01-09 13:57
On Jan 9, 2010, at 12:18 PM, Grant Ingersoll wrote:
For text, you can actually compute perplexity which measures how well cluster membership predicts what words are used. This is nice because you don't have to worry about the entropy of real valued numbers.
Do you have a good ref. on perplexity and/or some R code (or other)?
In looking a little more at this (via http://en.wikipedia.org/wiki/Perplexity), it seems we may already have most of this, given o.a.m.math.stats.LogLikelihood has the entropy calculation and this is just b^entropy() right? Or am I misreading? -Grant

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