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Machine learning as Granular Computing | IEEE Conference Publication | IEEE Xplore

Machine learning as Granular Computing


Abstract:

Zadeh proposed that there are three basic concepts that underlie human cognition: granulation, organization and causation and a granule being a clump of points (objects) ...Show More

Abstract:

Zadeh proposed that there are three basic concepts that underlie human cognition: granulation, organization and causation and a granule being a clump of points (objects) drawn together by indistinguishability, similarity, proximity or functionality. In this paper, we give out a novel definition of Granular Computing which can be easily treated by neural network. Perception learning as granular computing tries to study the machine learning from perception information sampling to dimensional reduction and samples classification in a granular way, and can be summaries as two kind approaches:(1) covering learning, (2) svm kind learning. We proved that although there are tremendous algorithms for dimensional reduction and information transformation, their ability can't transcend wavelet kind nested layered granular computing which are very easy for neural network processing.
Date of Conference: 17-19 August 2009
Date Added to IEEE Xplore: 22 September 2009
Print ISBN:978-1-4244-4830-2
Conference Location: Nanchang, China

References

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