現在地

イリチユ 美佳(イリチユ ミカ; Sato-Ilic, Mika)

研究者情報全体を表示

論文
  • Structural Classification based Correlation and its Application to Principal Component Analysis for High-Dimension Low-Sample Size Data
    Sato-Ilic Mika
    IEEE World Congress on Com- putational Intelligence/pp.981-988, 2012-01
  • An Adaptive Cluster-Target Covariance based Principal Component Analysis for Interval-Valued Data
    Sato-Ilic Mika
    IEEE World Congress on Computational Intelligence/pp.616-623, 2010
  • On weighted principal component analysis for interval-valued data and its dynamic feature
    Sato-Ilic Mika; Oshima Junya
    International Journal of Innovative Computing, Information and Control/2(1)/pp.69-82, 2006
  • An Adaptive Cluster-Target Covariance based Principal Component Analysis for Interval-Valued Data
    Sato-Ilic Mika
    FUZZ-IEEE2010, 2010-01
  • Individual Compositional Cluster Analysis
    Sato-Ilic Mika
    Procedia Computer Science/95/pp.254-263, 2016
  • Visualization of Fuzzy Clustering Result in Metric Space
    Sato-Ilic Mika; Ilic Peter
    Procedia Computer Sciences/96/pp.1666-1675, 2016
  • A Fuzzy Cluster Scaling Model
    Sato-Ilic Mika
    The 8th International Conference of the European Research Consortium for Informatics and Mathematics Working Group on Computational and Methodological Statistics/p.185, 2015-12
  • On A Variable Selection Method based on the Relationship between Discrimination Information and Principal Components
    Yamamoto Toshiki; Sato-Ilic Mika
    31st Fuzzy System Symposium/31/pp.75-80, 2015-09
  • Fuzzy Correlational Direction Multidimensional Scaling
    Sato-Ilic Mika
    Soft Computing Applications/2/pp.841-850, 2016
  • Clustering-based Models for High-dimensional Data
    Sato-Ilic Mika
    The 9th Conference of the Asian Regional Section of the International Association for Statistical Computing/pp.114-115, 2015-12
  • A Model of Cluster Loading and Its Application for a Variable Selection of High Dimension Low Sample Size Data
    J. Chen; Sato-Ilic Mika
    日本分類学会第34回大会/pp.6-8, 2016-03
  • 判定式に基づくカーネルk-means法
    辻 陽介; イリチユ 美佳
    日本分類学会第34回大会/pp.9-11, 2016-03
  • 外的基準を持つデータの主成分に基づく変数選択法
    山本 智基; イリチユ 美佳
    日本分類学会第34回大会/pp.18-20, 2016-03
  • 離島における分類構造を利用した人口減少に関する解析
    吉元 翔汰; イリチユ 美佳
    日本分類学会第34回大会/pp.31-33, 2016-03
  • Multidimensional Joint Scale and Cluster Analysis
    Sato-Ilic Mika
    Procedia Computer Science/61/pp.11-17, 2015-11
  • A variable selection method considering cluster loading for labeled high dimension low sample size data
    Jiaxin Chen; Sato-Ilic Mika
    Procedia Computer Science/60/pp.850-859, 2015
  • A Method for Interpreting Principle Components using Discrimination Information and Its Application to EEG Data
    Sato-Ilic Mika; T. Yamamoto
    Workshop on Statistical Methods for Large Complex Data/pp.45-51, 2014
  • A Fuzzy Clustering Method for Multi Source Data
    Sato-Ilic Mika; T. Hatori
    Workshop on Statistical Methods for Large Complex Data/pp.35-44, 2014
  • On a Multidimensional Cluster Scaling
    Sato-Ilic Mika; Ilic Peter
    Procedia Computer Sciences/36/pp.278-284, 2014
  • Universal Fuzzy Clustering Model
    Sato-Ilic Mika
    IEEE World Congress on Computational Intelligence/pp.2071-2078, 2014
  • A fuzzy clustering method using the relative structure of the belongingness of objects to clusters
    Hatori Tosei; Sato-Ilic Mika
    Procedia Computer Sciences/35/pp.994-1002, 2014
  • 分類構造に基づく相関分析
    イリチユ 美佳
    2013年度統計関連学会連合大会, 2013-09
  • Fuzzy Clustering Based Correlation and Its Application to Principal Component Analysis
    Sato-Ilic Mika
    the 59th ISI World Statistics Congress, 2013
  • Fuzzy Dissimilarity Based Multidimensional Scaling and Its Application to Collaborative Learning Data
    Sato-Ilic Mika; Ilic Peter
    Procedia Computer Science, Elsevier/20/pp.490-495, 2013
  • Two Covariances Harnessing Fuzzy Clustering Based PCA for Discrimination of Microarray Data
    Sato-Ilic Mika
    Lecture Notes in Bioinformatics, Springer-Verlag, Berlin Heidelberg (Germany), L.E. Peterson, F. Masulli, G. Russo, eds./pp.158-172, 2013