| Copyright | (c) Alexander Ignatyev 2016 |
|---|---|
| License | BSD-3 |
| Stability | experimental |
| Portability | POSIX |
| Safe Haskell | None |
| Language | Haskell2010 |
MachineLearning
Description
- addBiasDimension :: Matrix -> Matrix
- removeBiasDimension :: Matrix -> Matrix
- meanStddev :: Matrix Double -> (Matrix Double, Matrix Double)
- featureNormalization :: Fractional a => (a, a) -> a -> a
- mapFeatures :: Int -> Matrix -> Matrix
- splitToXY :: Element t => Matrix t -> (Matrix t, Vector t)
Documentation
addBiasDimension :: Matrix -> Matrix #
Add biad dimension to the future matrix
removeBiasDimension :: Matrix -> Matrix #
Remove biad dimension
meanStddev :: Matrix Double -> (Matrix Double, Matrix Double) #
Caclulates mean and stddev values of every feature. Takes feature matrix X, returns pair of vectors of means and stddevs.
featureNormalization :: Fractional a => (a, a) -> a -> a #
mapFeatures :: Int -> Matrix -> Matrix #
Maps the features into all polynomial terms of X up to the degree-th power