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Scale coarsening as feature selection

Published: 25 February 2008 Publication History

Abstract

We propose a unifying FCA-based framework for some questions in data analysis and data mining, combining ideas from Rough Set Theory, JSM-reasoning, and feature selection in machine learning. Unlike the standard rough set model the indiscernibility relation in our paper is based on a quasi-order, not necessarily an equivalence relation. Feature selection, though algorithmically difficult in general, appears to be easier in many cases of scaled many-valued contexts, because the difficulties can at least partially be projected to the scale contexts. We propose a heuristic algorithm for this.

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Cited By

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  • (2017)Three-way concept learning based on cognitive operatorsInternational Journal of Approximate Reasoning10.1016/j.ijar.2017.01.00983:C(218-242)Online publication date: 1-Apr-2017
  • (2014)Multi-adjoint fuzzy rough setsInternational Journal of Approximate Reasoning10.1016/j.ijar.2013.09.00755:1(412-426)Online publication date: 1-Jan-2014
  • (2014)The Structure of Oppositions in Rough Set Theory and Formal Concept Analysis - Toward a New Bridge between the Two SettingsProceedings of the 8th International Symposium on Foundations of Information and Knowledge Systems - Volume 836710.1007/978-3-319-04939-7_7(154-173)Online publication date: 3-Mar-2014
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Information & Contributors

Information

Published In

cover image Guide Proceedings
ICFCA'08: Proceedings of the 6th international conference on Formal concept analysis
February 2008
325 pages
ISBN:3540781366
  • Editors:
  • Raoul Medina,
  • Sergei Obiedkov

Sponsors

  • UQAM: Université du Québec à Montréal
  • Université du Québec
  • FQRNT: Le Fonds Québécois de la Recherche sur la Nature et les Technologies du Québec
  • CRIM: Centre de Rechercue Infromatique de Montreal
  • MITACS

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 25 February 2008

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Cited By

View all
  • (2017)Three-way concept learning based on cognitive operatorsInternational Journal of Approximate Reasoning10.1016/j.ijar.2017.01.00983:C(218-242)Online publication date: 1-Apr-2017
  • (2014)Multi-adjoint fuzzy rough setsInternational Journal of Approximate Reasoning10.1016/j.ijar.2013.09.00755:1(412-426)Online publication date: 1-Jan-2014
  • (2014)The Structure of Oppositions in Rough Set Theory and Formal Concept Analysis - Toward a New Bridge between the Two SettingsProceedings of the 8th International Symposium on Foundations of Information and Knowledge Systems - Volume 836710.1007/978-3-319-04939-7_7(154-173)Online publication date: 3-Mar-2014
  • (2013)A Formal Concept Analysis Based Approach to Minimal Value ReductionProceedings of the 8th International Conference on Rough Sets and Knowledge Technology - Volume 817110.1007/978-3-642-41299-8_11(109-120)Online publication date: 11-Oct-2013
  • (2010)Formal concept analysis in knowledge discoveryProceedings of the 18th international conference on Conceptual structures: from information to intelligence10.5555/1881168.1881185(139-153)Online publication date: 26-Jul-2010
  • (2007)Non-symmetric indiscernibilityProceedings of the First international conference on Knowledge processing and data analysis10.5555/2022767.2022770(26-34)Online publication date: 14-Sep-2007

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