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Mika Sato-Ilic
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2020 – today
- 2023
- [j8]Mika Sato-Ilic:
Fuzzy clustering based classifier for extraction of individualities from high dimension low sample size data. Intell. Decis. Technol. 17(1): 127-138 (2023) - [c46]Mika Sato-Ilic, Peter Ilic:
Fuzzy cluster-scaled principal component analysis for mixed data and its application of educational effect based on device selection. KES 2023: 2402-2411 - [c45]Yukako Toko, Mika Sato-Ilic:
Hierarchical Support Vector Machine based Classifier for Autocoding. KES 2023: 2733-2742 - 2022
- [p3]Mika Sato-Ilic:
Advances in Fuzzy Clustering Used in Indicator for Individuality. Advances in Selected Artificial Intelligence Areas 2022: 57-75 - 2021
- [c44]Kazuya Miyazawa, Mika Sato-Ilic:
A Classification Method Based on Ensemble Learning of Deep Learning and Multidimensional Scaling. KES-IDT 2021: 379-390 - [c43]Yukako Toko, Mika Sato-Ilic:
A Hybrid Method of Multi-class SVM and Classification Method Based on Reliability Score for Autocoding of the Family Income and Expenditure Survey. KES-IDT 2021: 403-413 - [c42]Kazuki Nitta, Mika Sato-Ilic:
Individual Difference Assessment Method Based on Cluster Scale Using a Data Reduction Method. KES-IDT 2021: 415-426 - [p2]Mika Sato-Ilic:
Fuzzy Clustering Models and Their Related Concepts. Fuzzy Approaches for Soft Computing and Approximate Reasoning 2021: 123-134 - 2020
- [c41]Yukako Toko, Mika Sato-Ilic:
Improvement of the Training Dataset for Supervised Multiclass Classification. KES-IDT 2020: 291-302 - [c40]Masao Takahashi, Tomoo Asakawa, Mika Sato-Ilic:
A Constrained Cluster Analysis with Homogeneity of External Criterion. KES-IDT 2020: 303-313
2010 – 2019
- 2019
- [c39]Mika Sato-Ilic:
Quantification and Visualization for Difference of Fuzzy Clustering Results. FUZZ-IEEE 2019: 1-6 - 2017
- [c38]Mika Sato-Ilic, Peter Ilic:
Cluster identification and scaling methods based on comparative quantification for dissimilarity data. FUZZ-IEEE 2017: 1-6 - 2016
- [c37]Mika Sato-Ilic, Peter Ilic:
Visualization of Fuzzy Clustering Result in Metric Space. KES 2016: 1666-1675 - 2015
- [c36]Mika Sato-Ilic:
Multidimensional Joint Scale and Cluster Analysis. Complex Adaptive Systems 2015: 11-17 - [c35]Jiaxin Chen, Mika Sato-Ilic:
A Variable Selection Method Considering Cluster Loading for Labeled High Dimension Low Sample Size Data. KES 2015: 850-859 - 2014
- [c34]Mika Sato-Ilic:
Part V: Data Science and Analytics Preface. Complex Adaptive Systems 2014: 276-277 - [c33]Mika Sato-Ilic, Peter Ilic:
On a Multidimensional Cluster Scaling. Complex Adaptive Systems 2014: 278-284 - [c32]Mika Sato-Ilic:
Universal fuzzy clustering model. FUZZ-IEEE 2014: 2071-2078 - [c31]Tosei Hatori, Mika Sato-Ilic:
A Fuzzy Clustering Method Using the Relative Structure of the Belongingness of Objects to Clusters. KES 2014: 994-1002 - [c30]Mika Sato-Ilic:
Fuzzy Correlational Direction Multidimensional Scaling. SOFA (2) 2014: 841-850 - 2013
- [j7]Chee Peng Lim, Canicious Abeynayake, Mika Sato-Ilic, Lakhmi C. Jain:
Special issue: Computational intelligence models for image processing and information reasoning. J. Intell. Fuzzy Syst. 24(2): 199-200 (2013) - [c29]Mika Sato-Ilic:
Part IV: Data Science and Analytics. Complex Adaptive Systems 2013: 420 - [c28]Mika Sato-Ilic, Peter Ilic:
Fuzzy Dissimilarity based Multidimensional Scaling and its Application to Collaborative Learning Data. Complex Adaptive Systems 2013: 490-495 - [c27]Takuya Izumi, Mika Sato, Yutaka Yabe, Yoshihiro Hagiwara, Yoshifumi Saijo:
Ultrasonic and photoacoustic imaging of knee joints in normal and osteoarthritis rats. EMBC 2013: 1116-1119 - 2012
- [j6]Tomoyuki Kuwata, Mika Sato-Ilic, Lakhmi C. Jain:
A learning based self-organized additive fuzzy clustering method and its application for EEG data. Int. J. Knowl. Based Intell. Eng. Syst. 16(1): 69-78 (2012) - [j5]Tetsuaki Kawase, Atsuko Maki, Akitake Kanno, Nobukazu Nakasato, Mika Sato, Toshimitsu Kobayashi:
Contralateral white noise attenuates 40-Hz auditory steady-state fields but not N100m in auditory evoked fields. NeuroImage 59(2): 1037-1042 (2012) - [c26]Mika Sato-Ilic:
Two Covariances Harnessing Fuzzy Clustering Based PCA for Discrimination of Microarray Data. CIBB 2012: 158-172 - [c25]Mika Sato-Ilic:
Structural classification based correlation and its application to principal component analysis for high-dimension low-sample size data. FUZZ-IEEE 2012: 1-8 - [c24]Mika Sato-Ilic:
Preface to Part III Adaptive Big Data Analytics. Complex Adaptive Systems 2012: 211 - [c23]Ryunosuke Chiba, Mika Sato-Ilic:
Analysis of Web Survey Data based on Similarity of Fuzzy Clusters. Complex Adaptive Systems 2012: 224-229 - [c22]Mika Sato-Ilic:
On Fuzzy Clustering based Correlation. Complex Adaptive Systems 2012: 230-235 - 2011
- [c21]Mika Sato-Ilic:
Generalized operators and its application to a nonlinear fuzzy clustering model. CIBCB 2011: 69-75 - [c20]Mika Sato-Ilic:
Symbolic Clustering with Interval-Valued Data. Complex Adaptive Systems 2011: 358-363 - 2010
- [c19]Mika Sato-Ilic:
An adaptive cluster-target covariance based principal component analysis for interval-valued data. FUZZ-IEEE 2010: 1-8 - [c18]Mika Sato-Ilic:
Dissimilarity Based Principal Component Analysis Using Fuzzy Clustering. IUM 2010: 453-464
2000 – 2009
- 2009
- [c17]Mika Sato-Ilic, Shota Ito, Shota Takahashi:
Generalized kernel fuzzy clustering model. FUZZ-IEEE 2009: 421-426 - 2008
- [c16]Mika Sato-Ilic:
Clustering objects with degree of classification. FUZZ-IEEE 2008: 1737-1744 - [p1]Mika Sato-Ilic:
Fuzzy Blocking Regression Models. Computational Intelligence Paradigms 2008: 195-217 - [e2]Lakhmi C. Jain, Mika Sato-Ilic, Maria Virvou, George A. Tsihrintzis, Valentina Emilia Balas, Canicious Abeynayake:
Computational Intelligence Paradigms, Innovative Applications. Studies in Computational Intelligence 137, Springer 2008, ISBN 978-3-540-79473-8 [contents] - 2007
- [c15]Mika Sato-Ilic, Lakhmi C. Jain:
Asymmetric Clustering Based on Self-Similarity. IIH-MSP 2007: 361-364 - [c14]Mika Sato-Ilic:
Weighted fuzzy clustering on subsets of variables. ISSPA 2007: 1-4 - [c13]Mika Sato-Ilic:
Variable Based Fuzzy Blocking Regression Model. KES (2) 2007: 525-532 - [e1]Javaan S. Chahl, Lakhmi C. Jain, Akiko Mizutani, Mika Sato-Ilic:
Innovations in Intelligent Machines - 1. Studies in Computational Intelligence 70, Springer 2007, ISBN 978-3-540-72695-1 [contents] - 2006
- [b2]Mika Sato-Ilic, Lakhmi C. Jain:
Innovations in Fuzzy Clustering - Theory and Applications. Studies in Fuzziness and Soft Computing 205, Springer 2006, ISBN 978-3-540-34356-1, pp. 1-145 [contents] - [j4]Mika Sato-Ilic:
Dynamic fuzzy clustering using fuzzy cluster loading. Int. J. Gen. Syst. 35(2): 209-230 (2006) - [c12]Mika Sato-Ilic, Toshiya Shijo:
Genralized fuzzy cluster loading model. FUZZ-IEEE 2006: 757-762 - [c11]Mika Sato-Ilic, Tomoyuki Kuwata:
Fuzzy Structural Classification Methods. KES (2) 2006: 102-109 - [c10]Mika Sato-Ilic, Lakhmi C. Jain:
Innovations in Soft Data Analysis. KES (2) 2006: 110-114 - 2005
- [c9]Mika Sato-Ilic, Tomoyuki Kuwata:
On Fuzzy Clustering Based Self-Organized Methods. FUZZ-IEEE 2005: 973-978 - 2004
- [c8]Mika Sato-Ilic:
Fuzzy clustering based weighted principal component analysis for interval-valued data considering uniqueness of clusters. SMC (3) 2004: 2297-2302 - 2003
- [c7]Mika Sato-Ilic:
Weighted principal component analysis for interval-valued data based on fuzzy clustering. SMC 2003: 4476-4482 - 2001
- [c6]Shinobu Tatsunami, Rie Kuwabara, Tomoko Hiroi, Hiroaki Matsui, Katsuyuki Fukutake, Junichi Mimaya, Kaneo Yamada, Mika Sato:
Survival and Viral Load in Four Groups of HIV-1 Infected Hemophiliacs Compared by Three-way Data Clustering. MedInfo 2001: 557-560 - 2000
- [c5]Mika Sato-Ilic:
Classification Based on Relational Fuzzy C-Means for 3-Way Data. ICEIS 2000: 217-221 - [c4]Mika Sato-Ilic:
On evaluation of clustering using homogeneity analysis. SMC 2000: 3588-3593
1990 – 1999
- 1999
- [j3]Mika Sato-Ilic:
On Dynamic Clustering Models for 3-way Data. J. Adv. Comput. Intell. Intell. Informatics 3(1): 28-35 (1999) - 1998
- [c3]Mika Sato, Yoshiharu Sato:
Asymmetry for dynamic fuzzy clustering models. KES (2) 1998: 93-99 - [c2]Mika Sato-Ilic:
A clustering model on similarities for dynamic changes. SMC 1998: 2756-2761 - 1997
- [b1]Mika Sato, Yoshiharu Sato, Lakhmi C. Jain:
Fuzzy clustering models and applications. Studies in Fuzziness and Soft Computing 9, Springer 1997, ISBN 978-3-7908-1026-4, pp. I-IX, 1-122 [contents] - 1995
- [j2]Mika Sato, Yoshiharu Sato:
On A General Fuzzy Additive Clustering Model. Intell. Autom. Soft Comput. 1(4): 439-448 (1995) - [c1]Mika Sato, Yoshiharu Sato, Lakhmi C. Jain:
General fuzzy clustering model and neural networks. Electronic Technology Directions 1995: 104-112 - 1994
- [j1]Mika Sato, Yoshiharu Sato:
On a multicriteria fuzzy Clustering Method for 3-Way Data. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2(2): 127-142 (1994)
Coauthor Index
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