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Data Mining from Large High-dimensional Data by Multiobjective Genetics-based Machine Learning

Research Project

Project/Area Number 16K00336
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Soft computing
Research InstitutionOsaka Prefecture University

Principal Investigator

Nojima Yusuke  大阪府立大学, 工学(系)研究科(研究院), 准教授 (10382235)

Project Period (FY) 2016-04-01 – 2019-03-31
Project Status Completed (Fiscal Year 2018)
Budget Amount *help
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Keywords知識獲得 / 多目的最適化 / 並列分散実装 / 遺伝的アルゴリズム / 大規模多属性データ
Outline of Final Research Achievements

In recent years, data science is one of the hottest topics in computer science. Various data mining techniques have been developed so far. Among them, our multiobjective genetics-based machine learning is a data mining technique which can generate a number of knowledge models with different accuracy and complexity by its single run. In this research, we improved its effectiveness for large and high-dimensional data sets from both algorithmic and implementation points of view. We also extend our multiobjective genetics-based machine learning for the analysis on mechanical design problems, image data classification problems and multi-label classification problems.

Academic Significance and Societal Importance of the Research Achievements

大規模多属性データからの知識獲得において,計算時間の短縮と得られた知識の分かりやすさは非常に重要である.本研究では,知識の精度と分かりやすさを同時に最適化する多目的遺伝的機械学習手法の高効率化を行った.また,これまでの数値データからの知識獲得だけでなく,様々な応用問題へと展開したことで,今後,解釈可能なAIの発展に寄与できると考えられる.

Report

(4 results)
  • 2018 Annual Research Report   Final Research Report ( PDF )
  • 2017 Research-status Report
  • 2016 Research-status Report
  • Research Products

    (14 results)

All 2018 2017 2016

All Presentation (14 results) (of which Int'l Joint Research: 9 results)

  • [Presentation] Multiobjective evolutionary data mining for performance improvement of evolutionary multiobjective optimization2018

    • Author(s)
      Y. Nojima, Y. Tanigaki, N. Masuyama, and H. Ishibuchi
    • Organizer
      2018 IEEE International Conference on Systems, Man, and Cybernetics
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Multiobjective evolutionary classifier design using class scores by a deep convolutional neural network2018

    • Author(s)
      Y. Nojima, S. Sakai, N. Masuyama, and H. Ishibuchi
    • Organizer
      PPSN 2018 Workshop on Evolutionary Machine Learning
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] マルチラベル分類に適応した多目的ファジィ遺伝的機械学習2018

    • Author(s)
      荒張巧樹,増山直輝,能島裕介,石渕久生
    • Organizer
      第12回進化計算シンポジウム2018
    • Related Report
      2018 Annual Research Report
  • [Presentation] Multiobjective Fuzzy Genetics-Based Machine Learning based on MOEA/D with its Modifications2017

    • Author(s)
      Y. Nojima, K. Arahari, S. Takemura, and H. Ishibuchi
    • Organizer
      2017 IEEE International Conference on Fuzzy Systems
    • Place of Presentation
      Naples, Italy
    • Year and Date
      2017-07-09
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] Michigan-style Fuzzy GBML with (1+1)-ES Generation Update and Multi-Pattern Rule Generation2017

    • Author(s)
      Y. Nojima, S. Takemura, K. Watanabe, and H. Ishibuchi
    • Organizer
      Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
    • Place of Presentation
      Otsu, Japan
    • Year and Date
      2017-06-27
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] Michigan-style fuzzy GBML with (1+1)-ES generation update and multi-pattern rule generation2017

    • Author(s)
      Y. Nojima, S. Takemura, K. Watanabe, and H. Ishibuchi
    • Organizer
      2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS)
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Multiobjective fuzzy genetics-based machine learning based on MOEA/D with its modifications2017

    • Author(s)
      Y. Nojima, K. Arahari, S. Takemura, and H. Ishibuchi
    • Organizer
      2017 IEEE International Conference on Fuzzy Systems
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] Multi-objective GAssist with NSGA-II2017

    • Author(s)
      H. Gao, Y. Nojima, and H. Ishibuchi
    • Organizer
      18th International Symposium on Advanced Intelligent Systems
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research
  • [Presentation] 複数サーバを用いた並列分散型ファジィ遺伝的機械学習によるビッグデータ処理2017

    • Author(s)
      武村周治, 能島裕介, 石渕久生
    • Organizer
      第13回進化計算学会研究会講演集
    • Related Report
      2017 Research-status Report
  • [Presentation] 多目的ファジィ遺伝的機械学習における並列分散実装の過学習に対する効果2016

    • Author(s)
      武村周治,能島裕介,石渕久生
    • Organizer
      第10回進化計算シンポジウム2016
    • Place of Presentation
      千葉県九十九里
    • Year and Date
      2016-12-10
    • Related Report
      2016 Research-status Report
  • [Presentation] 進化型多目的最適化により得られた解集合からの多目的知識獲得2016

    • Author(s)
      能島裕介,谷垣勇輝,石渕久生
    • Organizer
      第10回進化計算シンポジウム2016
    • Place of Presentation
      千葉県九十九里
    • Year and Date
      2016-12-10
    • Related Report
      2016 Research-status Report
  • [Presentation] Fitting and overfitting of multi-objective fuzzy genetics-based machine learning to training data2016

    • Author(s)
      H. Ishibuchi, S. Takemura, and Y. Nojima
    • Organizer
      7th International Symposium on Computational Intelligence and Industrial Applications
    • Place of Presentation
      Beijing, China
    • Year and Date
      2016-11-03
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] 多目的ファジィ遺伝的機械学習に特化したスカラー関数の提案2016

    • Author(s)
      荒張巧樹, 武村周治, 能島裕介, 石渕久生
    • Organizer
      第11回進化計算学会研究会
    • Place of Presentation
      兵庫県神戸
    • Year and Date
      2016-09-14
    • Related Report
      2016 Research-status Report
  • [Presentation] Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms2016

    • Author(s)
      Y. Nojima and H. Ishibuchi
    • Organizer
      2016 IEEE Congress on Evolutionary Computation
    • Place of Presentation
      Vancouver, Canada
    • Year and Date
      2016-07-24
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research

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Published: 2016-04-21   Modified: 2020-03-30  

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