The very nature of my data/experiments make it highly susceptible to
outliers/noisy-exemplars, and I'm looking for a way of reducing the
number of such from my database. Happily, the book (Data Mining)
discusses such a problem in the 6th chapter (pg 194-195), but does not
give much guidance on how this can be done with/in Weka; specifically,
what packages/algorithms/options to use ...
Suggestions are much welcome!
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