Title

The generalization capabilities of ARTMAP

Abstract

Bounds on the number of training examples needed to guarantee a certain level of generalization performance in the ARTMAP architecture are derived. Conditions are derived under which ARTMAP can achieve a specific level of performance assuming any unknown, but fixed, probability distribution on the training data. © 1997 IEEE.

Publication Date

12-1-1997

Publication Title

IEEE International Conference on Neural Networks - Conference Proceedings

Volume

2

Number of Pages

1068-1071

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ICNN.1997.616176

Socpus ID

0030650654 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0030650654

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