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...
| Main Author: | |
|---|---|
| Format: | Others |
| Language: | en |
| Published: |
1993
|
| 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> |
Internet
https://thesis.library.caltech.edu/3245/1/Higgins_cm_1993.pdfHiggins, 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>