A constructive unsupervised learning algorithm for clustering binary patterns

Di Wang, Narendra S. Chaudhari, Jagdish C. Patra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

We propose a Constructive Unsupervised Learning Algorithm (CULA) for Boolean Neural Networks based on geometrical expansion. CULA constructs two-layered (input and output layer) neural networks. We visualize output neurons in terms of hyperspheres. CULA results in fast learning because it determines if to add a new coming vertex to a neuron by its geometrical location, not by iterant computation. We illustrate CULA by using 101 instances in zoo database of Richard Forsyth, and compare our unsupervised clustering with clustering by biological experts given in the zoo database.

Original languageBritish English
Title of host publication2004 IEEE International Joint Conference on Neural Networks - Proceedings
Pages1381-1385
Number of pages5
DOIs
StatePublished - 2004
Event2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest, Hungary
Duration: 25 Jul 200429 Jul 2004

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume2
ISSN (Print)1098-7576

Conference

Conference2004 IEEE International Joint Conference on Neural Networks - Proceedings
Country/TerritoryHungary
CityBudapest
Period25/07/0429/07/04

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