hsgsom.cabal

Name:               hsgsom
Version:            0.2.0
Cabal-Version:      >= 1.6.0.3
Build-Type:         Simple
License:            BSD3
License-File:       LICENSE
Data-Files:         README
Author:             Stephan Günther
Maintainer:         Stephan Günther <gnn dot github at gmail dot com>
Category:           Data Mining, Clustering
Synopsis:           An implementation of the GSOM clustering algorithm.
Description:
  The growing self organising map (GSOM) algorithm is a clustering algorithm
  working on a set of n-dimensional numeric input vectors. It's output is a
  network of nodes laid out in two dimensions where each node has a weight
  vector associated with it. This weight vector has the same dimension as the
  input vectors and is meant to be intepreted as a cluster center, i.e. it
  represents those input vectors whose distance to the node's weight vector
  is minimal when compared to the distance to the other nodes weight vectors.
  See <http://en.wikipedia.org/wiki/GSOM> for an explanation of the algorithm.
  The algorithm was introduced in:

    Alahakoon, D., Halgamuge, S. K. and Sirinivasan, B. (2000)
    Dynamic Self Organizing Maps With Controlled Growth
    for Knowledge Discovery,
    IEEE Transactions on Neural Networks,
    Special Issue on Knowledge Discovery and Data Mining, 11, pp 601-614.

Library
  Build-Depends:    base >= 3 && < 5, containers, random, time, stm
  Exposed-Modules:  Data.Datamining.Clustering.Gsom,
                    Data.Datamining.Clustering.Gsom.Coordinates,
                    Data.Datamining.Clustering.Gsom.Input,
                    Data.Datamining.Clustering.Gsom.Lattice,
                    Data.Datamining.Clustering.Gsom.Node,
                    Data.Datamining.Clustering.Gsom.Parallel,
                    Data.Datamining.Clustering.Gsom.Phase

  GHC-Options:     -O2 -fvia-C -optc-O3