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Try dictionary trimming for feature selection #17

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bwbaugh opened this issue Mar 17, 2013 · 0 comments

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bwbaugh commented Mar 17, 2013

For multinomial naive bayes, I hear that feature selection is really just dictionary trimming. It might be useful to try:

Discard features that occur in less than a certain percentage of documents seen for a label.
Only use the features that are the top-N most frequent features for a label.

ghost assigned bwbaugh

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