Multitask Fuzzy Learning with Rule Weight

Zhen Xing Li; Wei Hua Li

doi:10.4028/www.scientific.net/AMR.774-776.1883

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 774-776Multitask Fuzzy Learning with Rule Weight

Multitask Fuzzy Learning with Rule Weight

Abstract:

In fuzzy learning system based on rule weight, certainty grade, denoted by membership function of fuzzy set, defines how close a rule to a classification. In this system, several rules can correspond to same classification. But it cannot reflect the changing while training several tasks simultaneously. In this paper, we propose multitask fuzzy learning based on error-correction, and define belonging grade to show how much a sample belongs to a rule. Experimental results demonstrate efficiency of multitask fuzzy learning, and multitask learning could help to improve learning machines prediction.

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Periodical:

Advanced Materials Research (Volumes 774-776)

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1883-1886

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.774-776.1883

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Online since:

September 2013

Authors:

Zhen Xing Li, Wei Hua Li

Keywords:

Fuzzy Learning, Multitask Learning, Rule Weight

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