name: som
version: 2.0
synopsis: Self-Organising Maps
description: A Kohonen Self-organising Map (SOM) maps input patterns
onto a regular grid (usually two-dimensional) where each
node in the grid is a model of the input data, and does
so using a method which ensures that any topological
relationships within the input data are also represented
in the grid. This implementation supports the use of
non-numeric patterns.
.
In layman's terms, a SOM can be useful when you you want
to discover the underlying structure of some data.
category: Math
cabal-version: >=1.8
build-type: Simple
author: Amy de Buitléir
copyright: (c) Amy de Buitléir 2010-2012
license: BSD3
stability: experimental
maintainer: amy@nualeargais.ie
license-file: LICENSE
library
hs-source-dirs: src
build-depends: base ==4.*,
base-unicode-symbols ==0.2.*,
binary == 0.5.*,
containers ==0.4.2.* || ==0.5.*,
grid ==3.*,
MonadRandom ==0.1.*
ghc-options: -Wall
exposed-modules: Data.Datamining.Clustering.SOM,
Data.Datamining.Clustering.SOMInternal
test-suite som-tests
type: exitcode-stdio-1.0
build-depends: base ==4.*,
test-framework-quickcheck2 == 0.3.*,
QuickCheck == 2.5.*,
test-framework == 0.8.*,
som,
grid ==3.*,
base-unicode-symbols ==0.2.*,
MonadRandom ==0.1.*,
random ==1.0.*
hs-source-dirs: test
ghc-options: -Wall
main-is: Main.hs