name: som version: 4.1 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. . The userguide is available at . 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.* || == 0.6.* || == 0.7.*, containers ==0.4.2.* || ==0.5.*, grid ==4.*, MonadRandom ==0.1.* ghc-options: -Wall exposed-modules: Data.Datamining.Clustering.SOM, Data.Datamining.Clustering.SOMInternal, Data.Datamining.Clustering.Classifier, Data.Datamining.Pattern test-suite som-tests type: exitcode-stdio-1.0 build-depends: base ==4.*, test-framework-quickcheck2 == 0.3.*, QuickCheck ==2.5.* || ==2.6.*, test-framework == 0.8.*, som, grid ==4.*, base-unicode-symbols ==0.2.*, MonadRandom ==0.1.*, random ==1.0.* hs-source-dirs: test ghc-options: -Wall main-is: Main.hs