SATO-ILIC Mika
- Articles
- 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 - 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 - 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 - Weighted Regression Analysis for Interval-Valued Compositional Data
藤本 聖; イリチユ 美佳
Proceedings of Japanese Classification Society Symposium 2021/pp.19, 1-19, 4, 2021-12 - Probabilistic Metric Based Multidimensional Scaling
Sato-Ilic Mika
Procedia Computer Science/168/pp.65-72, 2020-01 - 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 - Quantification and Visualization for Difference of Fuzzy Clustering Results
Sato-Ilic Mika
The 2019 IEEE International Conference on Fuzzy Systems,2019, 2019-06 - 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 - Generalization for Improvement of the Reliability Score for Autocoding
Toko Yukako; Iijima Shinya; Sato-Ilic Mika
ROMANIAN STATISTICAL REVIEW/(3)/pp.47-59, 2019 - 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 - Homogeneous Cluster Analysis
Sato-Ilic Mika
Procedia Computer Sciences/140/pp.269-275, 2018-11 - 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 - 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 - 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 - Knowledge-based Comparable Predicted Values in Regression Analysis
Sato-Ilic Mika
Procedia Computer Science, Elsevier/114/pp.216-223, 2017-11 - 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 - Overlapping classification for autocoding system
Toko Yukako; Iijima Shinya; Sato-Ilic Mika
ROMANIAN STATISTICAL REVIEW/(4)/pp.58-73, 2018 - 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 - 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 - Fuzzy Correlational Direction Multidimensional Scaling
Sato-Ilic Mika
Soft Computing Applications/2/pp.841-850, 2016 - A Model of Cluster Loading and Its Application for a Variable Selection of High Dimension Low Sample Size Data
J. Chen; Sato-Ilic Mika
the 34th Annual Research Meeting of the Japanese Classification Society/pp.6-8, 2016-03 - more...
- A Hybrid Method of Multi-class SVM and Classification Method Based on Reliability Score for Autocoding of the Family Income and Expenditure Survey