The Research of Key Data Classification Optimal Mining Methods for Massive Data

Yin Ying Li; Yun Ze Wang

doi:10.4028/www.scientific.net/AMR.989-994.2001

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994The Research of Key Data Classification Optimal...

The Research of Key Data Classification Optimal Mining Methods for Massive Data

Abstract:

The data classification is an important issue in massive data classification. This paper proposes an inter-cell classification algorithm based on phase recombination neighbor points convergence which analyzes the convergence value weights of inter-cell characteristic points and filter the interferences of the minority local optimal characteristic points. The proposed algorithm can promote the convergence of the inter-cell classification data neighbor points. The simulation experiments testify the models by three types of actually collected data sets which illustrate the models have better classification performance.

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Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

2001-2003

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.2001

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Online since:

July 2014

Authors:

Yin Ying Li, Yun Ze Wang*

Keywords:

Convergence, Fuzzy, Inter-Cell Classification, Mathematical Models

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