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Diffuse pattern learning with Fuzzy ARTMAP and PASS

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  • Muruzábal, Jorge
  • Muñoz, Alberto

Abstract

Fuzzy ARTMAP is compared to a classifier system (CS) called PASS (predictive adaptive sequential system). Previously reported results in a benchmark classification task suggest that Fuzzy ARTMAP systems perform better and are more parsimonious than systems based on the CS architecture. The tasks considered here differ from ordinary classificatory tasks in the amount of output uncertainty associated with input categories. To be successful, learning systems must identify not only correct input categories, but also the most likely outputs for those categories. Performance under various types of diffuse patterns is investigated using a simulated scenario.

Suggested Citation

  • Muruzábal, Jorge & Muñoz, Alberto, 1994. "Diffuse pattern learning with Fuzzy ARTMAP and PASS," DES - Working Papers. Statistics and Econometrics. WS 3821, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:3821
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    References listed on IDEAS

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    1. Muruzábal, Jorge, 1993. "PASS: a simple classifier system for data analysis," DES - Working Papers. Statistics and Econometrics. WS 3732, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Keywords

    Diffuseness;

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