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International Conference on Rough Sets and Knowledge Technology

RSKT 2015: Rough Sets and Knowledge Technology pp 175–187Cite as

Families of the Granules for Association Rules and Their Properties

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9436))

Abstract

We employed the granule (or the equivalence class) defined by a descriptor in tables, and investigated rough set-based rule generation. In this paper, we consider the new granules defined by an implication, and propose a family of the granules defined by an implication in a table with exact data. Each family consists of the four granules, and we show that three criterion values, support, accuracy, and coverage, can easily be obtained by using the four granules. Then, we extend this framework to tables with non-deterministic data. In this case, each family consists of the nine granules, and the minimum and the maximum values of three criteria are also obtained by using the nine granules. We prove that there is a table causing support and accuracy the minimum, and generally there is no table causing support, accuracy, and coverage the minimum. Finally, we consider the application of these properties to Apriori-based rule generation from uncertain data. These properties will make Apriori-based rule generation more effective.

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Acknowledgment

The authors would be grateful for reviewers’ useful comments. This work is supported by JSPS (Japan Society for the Promotion of Science) KAKENHI Grant Number 26330277.

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Authors and Affiliations

  1. Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, 804-8550, Japan

    Hiroshi Sakai & Chenxi Liu

  2. Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba, 283, Japan

    Michinori Nakata

Authors
  1. Hiroshi Sakai
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  2. Chenxi Liu
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  3. Michinori Nakata
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Corresponding author

Correspondence to Hiroshi Sakai .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  2. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  3. Indian Statistical Institute, Kolkata, India

    Sushmita Mitra

  4. Zhejiang Ocean University, Zhejiang, China

    Wei-Zhi Wu

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Sakai, H., Liu, C., Nakata, M. (2015). Families of the Granules for Association Rules and Their Properties. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham. https://doi.org/10.1007/978-3-319-25754-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-25754-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25753-2

  • Online ISBN: 978-3-319-25754-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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