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A method for data classification based on discernibility matrix and discernibility function

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Wuhan University Journal of Natural Sciences

Abstract

A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification.

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Author information

Authors and Affiliations

  1. School of Science, Southwest Jiaotong University, 610031, Chengdu Sichuan, China

    Sun Shi-bao & Qin Ke-yun

  2. Electronic Information Engineering College, Henan University of Science and Technology, 471003, Luoyang Henan, China

    Sun Shi-bao

Authors
  1. Sun Shi-bao
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  2. Qin Ke-yun
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Corresponding author

Correspondence to Qin Ke-yun.

Additional information

Foundation item: Supported by the National Natural Science Foundation of China (60474022).

Biography: SUN Shi-bao(1970-), male, Ph. D. candidate, Lecturer, research direction: intelligent information processing.

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Shi-bao, S., Ke-yun, Q. A method for data classification based on discernibility matrix and discernibility function. Wuhan Univ. J. Nat. Sci. 11, 230–233 (2006). https://doi.org/10.1007/BF02831737

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  • DOI: https://doi.org/10.1007/BF02831737

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