perf(word2vec): better word2vec
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@ -16,17 +16,17 @@ module Main where
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main = do
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sws <- lines <$> readFile "examples/stopwords"
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{-ds <- do-}
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{-content <- readFile "examples/doc-classifier-data/data-reuters"-}
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{-let splitted = splitOn (replicate 10 '-' ++ "\n") content-}
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{-d = concatMap (tail . lines) (take 100 splitted)-}
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{-return $ removeWords sws d-}
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{-ds <- do
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content <- readFile "examples/doc-classifier-data/data-reuters"
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let splitted = splitOn (replicate 10 '-' ++ "\n") content
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d = concatMap (tail . lines) (take 100 splitted)
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return $ removeWords sws d-}
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--let ds = ["I like deep learning", "I like NLP", "I enjoy flying"]
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let ds = ["the king loves the queen", "the queen loves the king",
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"the dwarf hates the king", "the queen hates the dwarf",
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"the dwarf poisons the king", "the dwarf poisons the queen"]
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let session = def { learningRate = 0.1
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let session = def { learningRate = 5e-2
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, batchSize = 1
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, epochs = 100
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, debug = True
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@ -1,7 +1,8 @@
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module Sibe.Utils
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(similarity,
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ordNub,
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onehot
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( similarity
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, ordNub
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, onehot
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, average
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) where
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import qualified Data.Vector.Storable as V
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import qualified Data.Set as Set
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@ -22,3 +23,6 @@ module Sibe.Utils
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go _ [] = []
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go s (x:xs) = if x `Set.member` s then go s xs
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else x : go (Set.insert x s) xs
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average :: Vector Double -> Vector Double
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average v = cmap (/ (V.sum v)) v
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@ -75,12 +75,15 @@ module Sibe.Word2Vec
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| i == length vocvec - 1 = before
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| otherwise = before ++ after
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vectorized = map (\w -> snd . fromJust $ find ((== w) . fst) vocvec) ns
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new = cmap (max 1) $ foldl1 (+) vectorized
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new = foldl1 (+) vectorized
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in
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case method w2v of
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SkipGram -> zip (repeat v) vectorized
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CBOW -> zip vectorized (repeat v)
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_ -> error "unsupported word2vec method"
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if length wds <= 1
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then []
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else
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case method w2v of
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SkipGram -> [(v, average new)]
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CBOW -> [(average new, v)]
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_ -> error "unsupported word2vec method"
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cleanText :: String -> String
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cleanText string =
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