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I'm not absolutely sure with regard to the other techniques, but feature correlation is a concern that should be tackled before assessing attribute value.
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That may be a ton of new binary variables. Your resulting dataset might be sparse (plenty of zeros). Characteristic choice prior could be a good idea, also try following.
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Obtaining irrelevant functions in the data can minimize the accuracy of numerous products, Specifically linear algorithms like linear and logistic regression.
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