7 resultados para Taylor rule

em Boston University Digital Common


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http://www.archive.org/details/somebyproductsof013993mbp

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$u http://books.google.com/books?vid=OCLC02623863&id=mQz8gPn0et8C&a_sbrr=1 View book via Google

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http://www.archive.org/details/aretrospect00tayluoft

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http://www.archive.org/details/calilifeillustrated00taylrich

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Boston University Theology Library

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This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those recognition nodes whose confidence index falls below a selected threshold; and quantization of continuous learned weights allows the final system state to be translated into a usable set of rules. Simulations on a medical prediction problem, the Pima Indian Diabetes (PID) database, illustrate the method. In the simulations, pruned networks about 1/3 the size of the original actually show improved performance. Quantization yields comprehensible rules with only slight degradation in test set prediction performance.