Kernel density estimator in W-NaiveBayes

Question

Hi,

does anybody know why W-NaiveBayes does not include the kernel density estimator like his similar in Weka? This option is only part of W-NaiveBayesUpdateable. The same issue concerns Rapidminer in-built NaiveBayes.

Thank you!

Matteo

land · Answer

Hi Matteo,
I don't know this learners algorithm since it's one of the weka learners. (As indicated by the "W-") But I assume, that it recalculates mean and variance of all attributes incrementally if another example is added.

Greetings,
  Sebastian

fosgene · Answer

Leaving for a while the issue about kernel density estimator, I tried W-NaiveBayesUpdateble but I can't understand how it works compared to ordinary NaiveBayes.
First of all, is the term Updateable a definition for an on-line algorithm? And about this, does it mean that NBUpd uses one istance at time, evaluates it, and adds its results to those of all past instances?
Second, the fact of attribute precision: how does it work? The help only says that "This classifier will use a default precision is 0.1 for numeric attributes when buildClassifier is called with zero training istances", but there is no explanation about its use.

Thanks for your help!

Matteo

land · Answer

hmm,
seems to be strange. I will check that and come back to you.

Greetings,
  Sebastian