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[会议论文]

A global discretization method based on clustering and rough set

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Author:

Luo, Hairui (Luo, Hairui.) | Yan, Jianzhuo (Yan, Jianzhuo.) | Fang, Liying (Fang, Liying.) | Unfold

Indexed by:

EI Scopus

Abstract:

Discretization is an important algorithm and considered to be a process of information generalization and data reduction. To avoid information loss and total number of cut point decrease after discretization of continuous attributes, based on multi-attribute discretization algorithm with good global clustering effects for selecting candidate cut points is proposed. The improved algorithm is combined with the advantages of clustering method and algorithm based on the importance of cut points, The experimental results show that the proposed algorithm can significantly decrease the number of discretization cut points and increase the predictive accuracy of the classifier than both. © 2014 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.

Keyword:

Soft computing Fuzzy logic Clustering algorithms Decision making Discrete event simulation

Author Community:

  • [ 1 ] [Luo, Hairui]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Yan, Jianzhuo]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Fang, Liying]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Wang, Hui]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Shi, Xinqing]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China

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Source :

Year: 2014

Page: 400-405

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

30 Days PV: 4

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