A classification algorithm of continuous domain decision table

  • Authors:

  • Liu Wenjun

  • Affiliations:

  • Department of Mathematics and Computing Science, Changsha University of Science and Technology, Changsha city in Hunan Province, China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
  • Year:
  • 2009

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Abstract

First, the definition of similarity degree of objects in continuous domain decision table is given; then, according to fuzzy clustering, an attribute reduct and attribute significance algorithm of continuous domain decision table is put forward; thirdly, a classification algorithm is proposed according to the principle of maximum membership degree; at last, the validity of this classification algorithm is accounted for through an example.