Classification and approximation with rule-based networks
This thesis describes the architecture of learning systems which can explain their decisions through a rule-based knowledge representation. Two problems in learning are addressed: pattern classification and function approximation. In Part I, a pattern classifier for discrete-valued problems is pres...
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| Format: | Others |
| Language: | en |
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1993
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| Online Access: | https://thesis.library.caltech.edu/3245/1/Higgins_cm_1993.pdf Higgins, Charles M. (1993) Classification and approximation with rule-based networks. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/4r7r-w573. https://resolver.caltech.edu/CaltechETD:etd-08272007-132407 <https://resolver.caltech.edu/CaltechETD:etd-08272007-132407> |