Rough sets meet statistics - a new view on rough set reasoning about numerical data

Marko Palangetić, Chris Cornelis, Salvatore Greco, Roman Słowiński

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

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Abstract

In this paper, we present a new view on how the concept of rough sets may be interpreted in terms of statistics and used for reasoning about numerical data. We show that under specific assumptions, neighborhood based rough approximations may be seen as statistical estimations of certain and possible events. We propose a way of choosing the optimal neighborhood size inspired by statistical theory. We also discuss possible directions for future research on the integration of rough sets and statistics.
Original languageEnglish
Title of host publicationRough Sets: IJCRS 2020
EditorsR. Bello, D. Miao, R. Falcon, M. Nakata, A. Rosete, D. Ciucci
PublisherSpringer
Chapter6
Pages78-92
Number of pages15
ISBN (Electronic)978-3-030-52705-1
ISBN (Print)978-3-030-52704-4
DOIs
Publication statusPublished - 7 Jul 2020
EventInternational Joint Conference on Rough Sets - Havana, Cuba
Duration: 29 Jun 20203 Jul 2020

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12179
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Joint Conference on Rough Sets
CountryCuba
CityHavana
Period29/06/203/07/20

Keywords

  • rough sets
  • statistical learning
  • neighbourhood based rough sets

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