The hsgsom package

[Tags: bsd3, library]

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 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.


Versions0.1.0, 0.2.0
Dependenciesbase, containers, random, stm, time
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
Downloads228 total (21 in last 30 days)




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