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2009 Fiscal Year Final Research Report

A Novel Learning Method Based on Combinatorial Feature of Data

Research Project

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Project/Area Number 20800045
Research Category

Grant-in-Aid for Young Scientists (Start-up)

Allocation TypeSingle-year Grants
Research Field Fundamental theory of informatics
Research InstitutionIshinomaki Senshu University

Principal Investigator

HARAGUCHI Kazuya  Ishinomaki Senshu University, 理工学部, 助教 (80453356)

Research Collaborator NAGAMOCHI Hiroshi  京都大学, 大学院・情報学研究科, 教授 (70202231)
Project Period (FY) 2008 – 2009
Keywordsアルゴリズム / 機械学習 / 情報可視化
Research Abstract

In this project, we have aimed at establishing a novel learning method based on combinatorial feature of data. For classification, an essential learning problem, we proposed a learning algorithm based on bipartite graph structure. In computational experiments, we observed that its learning ability is competitive with previous methods and is even superior in some special cases.

  • Research Products

    (8 results)

All 2011 2010 2009 2008

All Journal Article (5 results) (of which Peer Reviewed: 3 results) Presentation (3 results)

  • [Journal Article] Classification via Visualization of Sample-feature Bipartite Graphs2011

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Journal Title

      Department of Applied Mathematics and Physics, Kyoto University, Technical Reports

  • [Journal Article] Visual Analysis of Hierarchical Data Using 2. 5D Drawing with Minimum Occlusion2010

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Journal Title

      Department of Applied Mathematics and Physics, Kyoto University, Technical Reports

  • [Journal Article] Multiclass Visual Classifier Based on Bipartite Graph Representation of Decision Tables2010

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Journal Title

      Proc. LION 4 (LNCS 6073)

      Pages: 169-183

    • Peer Reviewed
  • [Journal Article] Bipartite graph representation of multiple decision table classifiers2009

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Journal Title

      Proc. SAGA 2009 (LNCS 5792)

      Pages: 46-60

    • Peer Reviewed
  • [Journal Article] Visualization can improve multiple decision table classifiers2009

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Journal Title

      Proc. MDAI 2009 (ISBN: 978-84-00-08851-4)

      Pages: 41-52

    • Peer Reviewed
  • [Presentation] Learning Classifier by Edge Crossing Minimization2010

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Organizer
      Int'l workshop on Multi-dimensional Visualization
    • Year and Date
      20100000
  • [Presentation] Visualized Multiple Decision Table Classifiers without Discretization2009

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Organizer
      4th Korea-Japan Workshop on Operations Research in Service Science
    • Year and Date
      20090000
  • [Presentation] Classification by Ordering Data Samples2008

    • Author(s)
      Kazuya Haraguchi, Seok-Hee Hong, Hiroshi Nagamochi
    • Organizer
      Kyoto RIMS Workshop on Acceleration and Visualization of Computation for Enumeration Problems (AVCEP08)
    • Year and Date
      20080000

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Published: 2011-06-18   Modified: 2016-04-21  

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