Rule extraction: From neural architecture to symbolic representation

This paper shows how knowledge, in the form of fuzzy rules, can be derived from a supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning, which simplifies the network structure by removing excessive recognition categories and weights; and quantization...

Full description

Saved in:
Bibliographic Details
Main Authors: CARPENTER, Gail A., TAN, Ah-hwee
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1995
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/6281
https://ink.library.smu.edu.sg/context/sis_research/article/7284/viewcontent/ARTMAP_Rule_Extraction_CS95.PDF
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English