artificial intelligence - parameter optimization for classifier algorithm -
it said different algorithms have different parameters. don't see true, if tree decision algorithm , naive bayesian algorithm, parameter each? can give me example..
if case doing 5-fold cross validation data going run using decision tree algorithm different bayesian?
also parameter optimization 5-fold cross validation. there way automatically determine set values key of parameters using weka?
since using weka, can see parameters each algorithm opening dataset in explorer
, going classify
, choosing algorithm , clicking on algorithm box. instance naive bayes classifier has parameters affect how deals continuous data (discretization or using kernel estimator)
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