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Stream data classification with real time learning of kernel matrix

Research Project

Project/Area Number 26330251
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Intelligent informatics
Research InstitutionPrefectural University of Hiroshima (2016)
Toyohashi University of Technology (2014-2015)

Principal Investigator

Okabe Masayuki  県立広島大学, 経営情報学部, 講師 (50362330)

Project Period (FY) 2014-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywordsカーネル行列学習 / アンサンブル学習 / 制約付きK-means / 制約付きk-means / ブースティング / 異常検知システム / 異常検知
Outline of Final Research Achievements

Kernel matrix learning is an indispensable technique for machine learning to make of high accuracy. In this research, we developed an algorithm of kernel matrix learning that can be applied to incremental stream data classification and then proposed an active learning method that selects candidate data pairs to be labeled as constraints. We verified the utility of our developed algorithms through the experiments of outlier detection from network traffic.

Report

(4 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • 2014 Research-status Report
  • Research Products

    (5 results)

All 2016 2015 2014

All Journal Article (1 results) (of which Peer Reviewed: 1 results) Presentation (4 results)

  • [Journal Article] ツイート投稿位置推定のための単語フィルタリング手法2015

    • Author(s)
      森國泰平, 吉田光男, 岡部正幸, 梅村恭司
    • Journal Title

      情報処理学会論文誌:データベース

      Volume: 8 Pages: 16-26

    • NAID

      120005681011

    • Related Report
      2015 Research-status Report
    • Peer Reviewed
  • [Presentation] 従属クラスタ動的生成機構を導入したMust-Link制約付きK-meansの提案2016

    • Author(s)
      井本 博之,岡部 正幸,高間 康史
    • Organizer
      第9回WI2研究会
    • Place of Presentation
      リクルート本社(東京都千代田)
    • Year and Date
      2016-12-02
    • Related Report
      2016 Annual Research Report
  • [Presentation] 信頼区間の下限値による確率推定を用いた企業名抽出2016

    • Author(s)
      中野翔平, 菊地真人, 吉田光男, 岡部正幸, 梅村恭司
    • Organizer
      第8回データ工学と情報マネジメントに関するフォーラム
    • Place of Presentation
      福岡県福岡市
    • Year and Date
      2016-02-29
    • Related Report
      2015 Research-status Report
  • [Presentation] 外れ値検出に基づく対話的ファイアウォールログ分析2014

    • Author(s)
      岡部 正幸、山田 誠二
    • Organizer
      第28回人工知能学会全国大会
    • Place of Presentation
      ひめぎんホール(愛媛県、松山市)
    • Year and Date
      2014-05-14
    • Related Report
      2014 Research-status Report
  • [Presentation] 非明示的フィードバックにより訓練データ選択を支援するインタラクションデザイン2014

    • Author(s)
      福永 度宗、山田 誠二、岡部 正幸
    • Organizer
      第28回人工知能学会全国大会
    • Place of Presentation
      ひめぎんホール(愛媛県、松山市)
    • Year and Date
      2014-05-14
    • Related Report
      2014 Research-status Report

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Published: 2014-04-04   Modified: 2018-03-22  

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