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2002 Fiscal Year Final Research Report Summary

Implementation of Explanatory-Rule Acquisition System from Data with Numeric and Symbolic Attributes

Research Project

Project/Area Number 12680393
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionOsaka Prefecture University

Principal Investigator

UMANO Motohide  Osaka Prefecture University, College of Integrated Arts and Sciences, Professor, 総合科学部, 教授 (10131616)

Co-Investigator(Kenkyū-buntansha) HAYASHI Isao  Hayashi Hannan University, Graduate School of Corporate Information, Professor, 経営情報学部, 教授 (70258078)
OKADA Makoto  Osaka Prefecture University, College of Integrated Arts and Sciences, Research Associates, 総合科学部, 助手 (40336813)
Project Period (FY) 2000 – 2002
Keywordsexpiatory-rule acquisition / fuzzy rule acquisition / numeric and symbolic attributes / fuzzy decison tree / data mining / fuzzy logic
Research Abstract

We propose a method to acquire explanatory fuzzy rules from a data set with numeric and symbolic attributes. Examples of acquired fuzzy rules are the followings:
Most data of {sex = male}{age = young} are {class = A} with coverage 0.91
Almost all data of {sex = female}{height = middle} are {class = B} with coverage 0.73
where "sex" and "class" are symbolic attributes and "age" and "height" are numeric ones, "young" and "middle" are fuzzy sets of attributes "age" and "height," respectively, and "most" is a fuzzy quantifier in the proportion.
Since a real data set includes noise and errors, we can not apply conventional methods studied in a various fields. We use a fuzzy ID3-based algorithm to generate a fuzzy decision tree for a specified class. From a decision tree, we extract a piece of fuzzy knowledge from a path of the root to a class node by evaluating its understandability (the number of nodes) and informativeness (coverage of the specified data). We have implemented a explanatory-rule acquisition system based on the method.

  • Research Products

    (13 results)

All Other

All Publications (13 results)

  • [Publications] M.Umano, T.Okada et al.: "Extraction of Quantified Fuzzy Rules from Numerical Data"Ninth IEEE International Conference on Fuzzy Systems. 1062-1067 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] K.Hori, M.Umano, et al.: "Fuzzy C4.5 for Generating Fuzzy Decision Trees and Its Improvement"Fourth Asian Fuzzy Systems Symposium. 881-884 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] J.Deng, T.Oda, M.Umano: "Fuzzy Logical Operations in the Two-dimentional Hyper Logic Concerning the Fuzzy-set Concurrent Rating Method"Journal of Japan Association for Management Systems. 17・2. 33-42 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 林, 前田: "TAM Networkによるファジィルール獲得"阪南大学情報科学研究. 15. 22-33 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] M.Umano, Y.Matsumoto, et al.: "Learning by Switching Generation and Reasoning Methods in Several Knowledge Representations"Eleventh IEEE International Conference on Fuzzy Systems. 809-814 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 馬野 元秀: "ファジィとソフトコンピューティング ハンドブック(分担執筆)"共立出版. 390-416 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 林 勲, 筒井 茂義: "ファジィ・ニューラルネット・遺伝的アルゴリズム(分担執筆)"オーム社. 68-97 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] M. Umano, T. Okada, I. Hatono and H. Tamura: "Extraction of Quantified Fuzzy Rules from Numerical Data"Ninth IEEE International Conference on Fuzzy Systems. 1062-1067 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] K. Hori, M. Umano, H. Satoh and Y. Uno: "Fuzzy C4.5 for Generating Fuzzy Decision Trees and Its Improvement"Fourth Asian Fuzzy Systems Symposium (Tsukuba Science City, Japan, May 31 - June 3, 2000). 881-884 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] J. Deng, T. Oda and M. Umano: "Fuzzy Logical Operations in the Two-dimentional Hyper Logic Concerning the Fuzzy-set Concurrent Rating Method"Journal of Japan Association for Management Systems. 17-2. 33-42 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I. Hayashi and J.R. Williamson: "Acquisition of Fuzzy Knowledge from Topographic Mixture Networks with Attentional Feedback"International Joint Conference on Neural Networks (Washington DC, USA, July 15-19, 2001). 1386-1391 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] M. Umano, Y. Matsumoto, Y. Uno and K. Seta: "Learning by Switching Generation and Reasoning Methods in Several Knowledge Representations - towards the Simulation of Human Learning Process"Eleventh IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence) (Honolulu, Hawaii, USA, May 12 - 17, 2002). 809-814 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] I. Hayashi and J.R. Williamson: "An Analysis of Aperture Problem Using Fuzzy Rules Acquired from TAM Network"Eleventh IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence) (Honolulu, USA, May 12-17, 2002). 914-919 (2002)

    • Description
      「研究成果報告書概要(欧文)」より

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Published: 2004-04-14  

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