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Experimental Haskell machine learning library
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Mahdi Dibaiee 26eb4531fa feat(naivebayes): implement NaiveBayes algorithm 
feat(example): a document classifier using NaiveBayes over reuters data
2016-07-29 16:16:44 +04:30
app feat(crossEntropy): crossEntropy cost function 2016-07-24 10:48:04 +04:30
examples feat(naivebayes): implement NaiveBayes algorithm 2016-07-29 16:16:44 +04:30
src feat(naivebayes): implement NaiveBayes algorithm 2016-07-29 16:16:44 +04:30
test fix(stack): use stack build and exec instead of manual stack ghc 2016-07-18 16:33:34 +04:30
.gitignore Initial commit 2016-07-17 16:52:16 +04:30
LICENSE fix(stack): use stack build and exec instead of manual stack ghc 2016-07-18 16:33:34 +04:30
Setup.hs initial commit, still work in progress 2016-07-17 16:53:13 +04:30
sibe.cabal feat(naivebayes): implement NaiveBayes algorithm 2016-07-29 16:16:44 +04:30
stack.yaml fix(stack): use stack build and exec instead of manual stack ghc 2016-07-18 16:33:34 +04:30