Effective Population and Training Data Partitioning in Parallel Distributed Evolutionary Knowledge Acquisition

• Project/Area Number: 22700239
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Single-year Grants
• Research Field: Sensitivity informatics/Soft computing
• Research Institution: Osaka Prefecture University
• Principal Investigator: NOJIMA Yusuke 大阪府立大学, 大学院・工学研究科, 助教 (10382235)
• Project Period (FY): 2010 – 2012
• Project Status: Completed (Fiscal Year 2012)
• Budget Amount: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000); Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000); Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000); Fiscal Year 2010: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
• Keywords: 遺伝的アルゴリズム / 知識獲得 / 並列分散実装 / 進化計算 / 多目的最適化 / ファジィシステム / 遺伝的機械学習

Research Abstract

Evolutionary knowledge acquisition has beenproposed in order to obtain rule-based knowledge from numerical data. The main problem of this method is that huge computation cost is necessarywhen we apply it to large data. This study proposes parallel distributed implementation of evolutionary knowledge acquisition where both a population and training data are divided into subpopulations and training data subsets, respectively. The computational experiments show that the computational cost can be drastically reduced without the deterioration of the generalization ability. The effects of various specifications for parallel distributed implementation are also examined.

Research Products

• [Journal Article] Parallel distributed hybrid fuzzy GBML models with rule set migration and training data rotation (2013)
  • Author(s): H. Ishibuchi, S. Mihara, and Y. Nojima
  • Journal Title: IEEE Transactions on Fuzzy Systems Volume: 21 Pages: 355-368
  • Peer Reviewed
• [Presentation] Ensemble fuzzy rule-based classifier design by parallel distributed fuzzy GBML algorithms (2012)
  • Author(s): H. Ishibuchi, M. Yamane, and Y. Nojima
  • Organizer: Proc. of 9th International Conference on Simulated Evolution and Learning - SEAL 2012
  • Place of Presentation: Hanoi, Vietnam
  • Year and Date: 2012-12-19
• [Presentation] 並列分散型ファジィ遺伝的機械学習によるアンサンブル識別器の設計 (2012)
  • Author(s): 山根優和,能島裕介,石渕久生
  • Organizer: 第28回ファジィシステムシンポジウム
  • Place of Presentation: 名古屋
  • Year and Date: 2012-09-14
• [Presentation] Application of parallel distributed genetics-based machine learning toimbalanced data sets (2012)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: Proc. of 2012 IEEE International Conference on Fuzzy Systems
  • Place of Presentation: Brisbane, Australia
  • Year and Date: 2012-06-15
• [Presentation] Application of parallel distributed genetics-based machine learning to imbalanced data sets (2012)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: 2012 IEEE International Conference on Fuzzy Systems
  • Place of Presentation: Brisbane, Australia
• [Presentation] Ensemble fuzzy rule-based classifier design by parallel distributed fuzzy GBML algorithms (2012)
  • Author(s): H. Ishibuchi, M. Yamane, and Y. Nojima
  • Organizer: 9th International Conference on Simulated Evolution and Learning
  • Place of Presentation: Hanoi, Vietnam
• [Presentation] 並列分散型ファジィ遺伝的機械学習によるアンサンブル識別器の設計 (2012)
  • Author(s): 山根優和，能島裕介，石渕久生
  • Organizer: 第28回ファジィシステムシンポジウム
  • Place of Presentation: 名古屋，愛知県
• [Presentation] Training data subdivision and periodical rotation in hybrid fuzzy genetics-based machine learning (2011)
  • Author(s): H. Ishibuchi, S. Mihara, and Y. Nojima
  • Organizer: Proc. of 10th International Conference on Machine Learning and Applications
  • Place of Presentation: Honolulu, Hawaii, USA
  • Year and Date: 2011-12-21
• [Presentation] 並列分散型遺伝的機械学習における環境の変化が及ぼす汎化性能への影響 (2011)
  • Author(s): 三原新吾,能島裕介,石渕久生
  • Place of Presentation: 宮城
  • Year and Date: 2011-12-18
• [Presentation] Parallel distributed genetic rule selection of association rules (2011)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: Abstract Booklet of International Workshop on Simulation and Modeling related to Computational Science and Robotics Technology
  • Place of Presentation: Kobe, Japan
  • Year and Date: 2011-11-03
• [Presentation] Relation between migration interval and data rotation interval in parallel distributed fuzzy GBML (2011)
  • Author(s): S. Mihara. Y. Nojima, and H. Ishibuchi
  • Organizer: Proc. of 12th International Symposium on Advanced Intelligent Systems
  • Place of Presentation: Suwon, Korea
  • Year and Date: 2011-10-01
• [Presentation] 並列分散型ファジィ遺伝的機械学習の探索性能に対する個体移住操作の影響 (2011)
  • Author(s): 三原新吾,能島裕介,石渕久生
  • Organizer: 第21回インテリジェント・システム・シンポジウム講演論文集
  • Place of Presentation: 神戸
  • Year and Date: 2011-09-14
• [Presentation] Relation between migration interval and data rotation interval in parallel distributed fuzzy GBML (2011)
  • Author(s): S.Mihara, Y.Nojima, H.Ishibuchi
  • Organizer: 12th International Symposium on Advanced Intelligent Systems
  • Place of Presentation: La Vie D'OR Resort Suwon・韓国
• [Presentation] Parallel distributed genetic rule selection of association rules (2011)
  • Author(s): Y.Nojima, S.Mihara, H.Ishibuchi
  • Organizer: International Workshop on Simulation and Modeling related to Computational Science and Robotics Technology
  • Place of Presentation: 神戸大学神戸・日本
• [Presentation] Training data subdivision and periodical rotation in hybrid fuzzy genetics-based machine learning (2011)
  • Author(s): H.Ishibuchi, S.Mihara, Y.Nojima
  • Organizer: 10th International Conference on Machine Learning and Applications
  • Place of Presentation: Hilton Hawaiian Villageホノルル・米国
• [Presentation] 並列分散型ファジィ遺伝的機械学習の探索性能に対する個体移住操作の影響 (2011)
  • Author(s): 三原新吾, 能島裕介, 石渕久生
  • Organizer: 第21回インテリジェント・システム・シンポジウム
  • Place of Presentation: 神戸大学・兵庫
• [Presentation] 並列分散型遺伝的機械学習における環境の変化が及ぼす汎化性能への影響 (2011)
  • Author(s): 三原新吾, 能島裕介, 石渕久生
  • Organizer: 進化計算シンポジウム2011
  • Place of Presentation: モンタナリゾート岩沼・宮城
• [Presentation] Parallel distributed implementation of genetics-based machine learning for fuzzy classifier design (2010)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: Lecture Notes in Computer Science 6457: Simulated Evolution and Learning (8th International Conference on Simulated Evolution and Learning)
  • Place of Presentation: Springer, Berlin
  • Year and Date: 2010-12-04
• [Presentation] Parallel distributed implementation of genetics-based machine learning for fuzzy classifier design (2010)
  • Author(s): Y.Nojima, S.Mihara, H.Ishibuchi
  • Organizer: 8th International Conference on Simulated Evolution and Learning
  • Place of Presentation: Indian Institute of Technology Kanpur,インド・カンプール
  • Year and Date: 2010-12-01
• [Presentation] Rotation effect of training data subsets in parallel distributed fuzzy genetics-based machine learning (2010)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: Proc. of 14th Asia Pacific Symposium on Intelligent and Evolutionary Systems
  • Place of Presentation: Miyajima, Japan
  • Year and Date: 2010-11-20
• [Presentation] Rotation effect of training data subsets in parallel distributed fuzzy genetics-based machine learning (2010)
  • Author(s): Y.Nojima, S.Mihara, H.Ishibuchi
  • Organizer: 14th Asia Pacific Symposium on Intelligent and Evolutionary Systems
  • Place of Presentation: 国民宿舎杜の宿 広島県・宮島
  • Year and Date: 2010-10-19
• [Presentation] Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets (2010)
  • Author(s): Y. Nojima, S. Mihara, and H. Ishibuchi
  • Organizer: Proc. of 2010 IEEE Congress on Evolutionary Computation
  • Place of Presentation: Barcelona, Spain
  • Year and Date: 2010-07-23
• [Presentation] Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets (2010)
  • Author(s): Y.Nojima, S.Mihara, H.Ishibuchi
  • Organizer: 2010 IEEE Congress on Evolutionary Computation
  • Place of Presentation: Centre de Conventions Internacional de Barcelona,スペイン・バルセロナ
  • Year and Date: 2010-07-18
• [Remarks]
  • URL: http://www.cs.osakafu-u.ac.jp/~nojima/