Keywords
learning algorithm, self-organizing networks
Abstract
This paper presents i-AA1*, a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1*, learning consists of adapting the nodes’ functions and the network’s overall topology as each new training pattern is presented. Provided the training data is consistent, computational complexity is low and prior factual knowledge may be used to “prime” the network and improve its predictive accuracy. Empirical generalization results on both toy problems and more realistic tasks demonstrate promise.
Original Publication Citation
Giraud-Carrier, C., and Martinez, T. R., "A Constructive Incremental Learning Algorithm for Binary Classification Tasks", Proceedings of SMCals/6, pp. 213-218, 26.
BYU ScholarsArchive Citation
Giraud-Carrier, Christophe G. and Martinez, Tony R., "A Constructive Incremental Learning Algorithm for Binary Classification Tasks" (2006). Faculty Publications. 1293.
https://scholarsarchive.byu.edu/facpub/1293
Document Type
Presentation
Publication Date
2006-07-26
Permanent URL
http://hdl.lib.byu.edu/1877/2407
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
© 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
http://lib.byu.edu/about/copyright/