SATO-ILIC Mika

Researcher's full information

Articles

• Discrimination of the Labeled High-Dimension Low-Sample Data for Healthcare
  Sato-Ilic Mika
  Proceedings of International Conference on FIM-IMIP-UMSO/pp.61-62, 2021/12
• Cluster-scaled principal component analysis
  Sato-Ilic Mika
  WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS/Epub/pp.1-13, 2021-10
• Principal Component Analysis for Fuzzy Interval-Valued Data
  益居 秀; イリチユ 美佳
  Proceedings of the 37th Fuzzy System Symposium/pp.393-398, 2021-09
• Hybrid autocoding method for the Family Income and Expenditure Survey
  床　裕佳子; イリチユ 美佳
  Proceedings of the 40th Japanese Classification Society Annual Research Meeting/pp.08, 1-08, 4, 2021-07
• A Hybrid Method of Multi-class SVM and Classification Method Based on Reliability Score for Autocoding of the Family Income and Expenditure Survey
  Toko Yukako; Sato-Ilic Mika
  Intelligent Decision Technologies, Smart Innovation, Systems and Technologies/pp.403-413, 2021-06
• Individual Difference Assessment Method Based on Cluster Scale Using a Data Reduction Method
  Nitta Kazuki; Sato-Ilic Mika
  Intelligent Decision Technologies, Smart Innovation, Systems and Technologies/238/pp.415-426, 2021-06
• A Classification Method Based on Ensemble Learning of Deep Learning and Multidimensional Scaling
  Miyazawa Kazuya; Sato-Ilic Mika
  Intelligent Decision Technologies, Smart Innovation, Systems and Technologies/238/pp.379-390, 2021-06
• Indicator for Individuality of Subjects Based on Similarity of Objects
  Sato-Ilic Mika
  Procedia Computer Science/185/pp.193-202, 2021-06
• Efficient Autocoding Method in High Dimensional Space
  Toko Yukako; Sato-Ilic Mika
  Romanian Statistical Review/1/pp.3-16, 2021-03
• A Constrained Cluster Analysis with Homogeneity of External Criterion
  Takahashi Masao; Asakawa Tomoo; Sato-Ilic Mika
  Intelligent Decision Technologies/193/pp.303-313, 2020-06
• Improvement of the Training Dataset for Supervised Multiclass Classification
  Toko Yukako; Sato-Ilic Mika
  Intelligent Decision Technologies/193/pp.291-302, 2020-06
• Probabilistic Metric Based Multidimensional Scaling
  Sato-Ilic Mika
  Procedia Computer Science/168/pp.65-72, 2020-01
• Evaluation of Fuzzy Clustering for High-Dimensional Data based on Principal Component Analysis
  村山喬則; イリチユ 美佳
  35th Fuzzy System Symposium/35/pp.203-208, 2019-08
  
  CiNii
• Fuzzy Clustering and Fuzzy Clustering Models
  佐藤美佳（イリチユ 美佳）
  Journal of Japan Society for Fuzzy Theory and Intelligent Informatics/31(3)/pp.75-81, 2019-06
• Quantification and Visualization for Difference of Fuzzy Clustering Results
  Sato-Ilic Mika
  The 2019 IEEE International Conference on Fuzzy Systems,2019, 2019-06
• Generalization for Improvement of the Reliability Score for Autocoding
  Toko Yukako; Iijima Shinya; Sato-Ilic Mika
  ROMANIAN STATISTICAL REVIEW/(3)/pp.47-59, 2019
• Homogeneous Cluster Analysis
  Sato-Ilic Mika
  Procedia Computer Sciences/140/pp.269-275, 2018-11
• Multilayer Clustering based on T-norms for High-Dimension Low-Sample Size Data
  伊藤佳輝; 元田卓; イリチユ 美佳
  第34回ファジィシステムシンポジウム講演論文集/pp.480-485, 2018-09
• Estimation of Business Demography Statistics: A Method for Analyzing Job Creation and Destruction
  Takahashi Masao; Sato-Ilic Mika; Okamoto Motoi
  Intelligent Decision Technologies 2018/97/pp.33-43, 2018-06
• Supervised Multiclass Classifier for Autocoding Based on Partition Coefficient
  Toko Yukako; Wada Kazumi; Iijima Shinya; Sato-Ilic Mika
  Intelligent Decision Technologies 2018/97/pp.54-64, 2018-06
• Cluster-Scaled Regression Analysis for High-Dimension and Low-Sample Size Data
  Sato-Ilic Mika
  Advances in Smart Systems Research/7(1)/pp.1-10, 2018-06
• Overlapping classification for autocoding system
  Toko Yukako; Iijima Shinya; Sato-Ilic Mika
  ROMANIAN STATISTICAL REVIEW/(4)/pp.58-73, 2018
• Knowledge-based Comparable Predicted Values in Regression Analysis
  Sato-Ilic Mika
  Procedia Computer Science, Elsevier/114/pp.216-223, 2017-11
• A Simultaneous Fuzzy Clustering Method for 3-Way Multi-Source Data
  イリチユ 美佳; 矢吹健二
  Proceedings of the Fuzzy System Symposium/33/pp.441-446, 2017-09
  
  CiNii
• Cluster Identification and Scaling Methods based on Comparative Quantification for Dissimilarity Data
  Sato-Ilic Mika; Ilic Peter
  The 2017 IEEE International Conference on Fuzzy Systems, 2017-07
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