hsgsom-0.1.0: An implementation of the GSOM clustering algorithm.

The hsgsom package

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.

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Versions0.1.0, 0.2.0
Dependenciesbase, containers, random, stm, time
LicenseBSD3
AuthorStephan Günther
MaintainerStephan Günther <gnn dot github at gmail dot com>
CategoryData Mining, Clustering
Upload dateMon Apr 27 21:59:36 UTC 2009
Uploaded byStephanGuenther
Built onghc-6.10, ghc-6.12, ghc-7.0

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