Haskell Artificial Neural Networking library
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  1. {-# LANGUAGE DeriveDataTypeable #-}
  2. import System.Console.CmdArgs.Implicit
  3. data CostFunction = Quadratic | CrossEntropy
  4. deriving (Show, Data)
  5. data Sample = Sample { lambda :: Double, eta :: Double, fileName :: String,
  6. costFunction :: CostFunction }
  7. deriving (Show, Data, Typeable)
  8. sample = Sample { lambda = 5 &= help "Lambda value for regularization",
  9. eta = 0.5 &= help "Learning rate",
  10. fileName = "" &= help "Load from file",
  11. costFunction = Quadratic &= help "Cost function" }
  12. &= summary "Sample v2"
  13. main = print =<< cmdArgs sample