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GECCO
2005
Springer

RABNET: a real-valued antibody network for data clustering

11 years 10 months ago
RABNET: a real-valued antibody network for data clustering
This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demonstrates robustness in the initial experiments reported here for a benchmark problem. Comparisons with results from the literature are also provided. To automatically segment the resultant neurons at the output, a tool from graph theory was used with promising results. General discussions and avenues for future works are also provided. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning - connectionism and neural nets, I.5.3 [Pattern Recognition]: Clustering – Algorithms; General Terms Algorithms, Design. Keywords Artificial Immune Systems, Data Clustering, Artificial Neural Networks
Helder Knidel, Leandro Nunes de Castro, Fernando J
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Helder Knidel, Leandro Nunes de Castro, Fernando J. Von Zuben
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