Supervised adaptive resonance theory and rules

Supervised adaptive resonance theory and rules

Supervised Adaptive Resonance Theory is a family of neural networks that performs incremental supervised learning of recognition categories (pattern classes) and multidimensional maps of both binary and analog patterns. This chapter highlights that the supervised ART architecture is compatible with...

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Bibliographic Details
Main Author: TAN, Ah-hwee
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2000
Subjects:
Choice Function
Category Node
Confidence Factor
Category Choice
Fuzzy ARTMAP
Computer and Systems Architecture
Databases and Information Systems
OS and Networks
Online Access:https://ink.library.smu.edu.sg/sis_research/5234
https://ink.library.smu.edu.sg/context/sis_research/article/6237/viewcontent/SART_rule.pdf
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Institution: Singapore Management University
Language: English
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