= README This is the README file of hsgsom, a haskell library implementing the growing self organising map clustering algorithm. == The Algorithm 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. == License This package and its contents are licensed under the BSD 3 clause license. You should have received a file called LICENSE containing said license along with this package. == Versioning This README correponds to version 0.1.0 of hsgsom, so as you can see it is a very early version. Version numbers follow the pattern X.Y.Z and have the following meaning: - a change in Z corresponds to minor changes as in documentation changes or changes to the underlying implementation - a change in Y correponds to added functionality and/or backwards compatible interface changes/additions. - a change in X correpsonds to a major implementation change either drastically changing the algorithm behaviour or performance or changing the interface in a possibly not backwards compatible way. == Questions, Bugs, etc... If you think you have found a bug, or you have questions or suggestions or really anything to say about the package it would be greatly appreciated if you would drop me a note or an email. This is my very firt attempt at packaging and releasing a substantial amount my own code to the public and I'm eager to learn how to do thinks better. Thanks for using/looking at this package and have a nice day.