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...
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Main Authors: | , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
1995
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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 |
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Institution: | Singapore Management University |
Language: | English |