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Incremental Reducts Based on Nearest Neighbor Relations and Linear Classifications

  • Naohiro Ishii
  • , Ippei Torii
  • , Kazunori Iwata
  • , Kazuya Odagiri
  • , Toyoshiro Nakashima
  • , Tokuro Matsuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dimension or variables reduction of data is an important problem and the reduction is needed for the analysis of higher dimensional data in the application domain. Rough set is fundamental and useful to reduce higher dimensional data to lower one for the classification. We develop a generation method of incremental reducts based on nearest neighbor relations and linear classifications using added data. First, the nearest neighbor relation is shown to play a fundamental role for the approximated reducts. Next, the complete reducts are generated on the degenerate convex cones, in which edge operations are performed. Finally, the incremental reducts are generated using the linear classification and the nearest neighbor relations on the convex cones.

Original languageEnglish
Title of host publicationProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages528-533
Number of pages6
ISBN (Electronic)9781728126272
DOIs
Publication statusPublished - 07-2019
Externally publishedYes
Event8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 - Toyama, Japan
Duration: 07-07-201911-07-2019

Publication series

NameProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019

Conference

Conference8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019
Country/TerritoryJapan
CityToyama
Period07-07-1911-07-19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Social Sciences (miscellaneous)

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