Advanced Studies in Classification and Data Science. 1st ed. 2020

種類:

電子ブック

責任表示:

edited by Tadashi Imaizumi, Akinori Okada, Sadaaki Miyamoto, Fumitake Sakaori, Yoshiro Yamamoto, Maurizio Vichi

出版情報:

Singapore : Springer Nature Singapore : Imprint: Springer, 2020

著者名:

Imaizumi, Tadashi.

Okada, Akinori.

Miyamoto, Sadaaki.

Sakaori, Fumitake.

Yamamoto, Yoshiro.

Vichi, Maurizio.

SpringerLink (Online service)

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シリーズ名:

Studies in Classification, Data Analysis, and Knowledge Organization ;

ISBN:

9789811533112 [9811533113]    

注記:

Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment -- Chapter 2. Multi-citeria classifications in regional development modelling -- Chapter 3. Non-parametric latent modeling and network clustering -- Chapter 4. Efficient, Geometrically-adaptive Techniques for Multiscale Gaussian-kernel SVM Classification -- Chapter 5. Random forests followed by computed ABC analysis as a feature selection method for machine-learning in biomedical data -- Chapter 6. Non-Hierarchical Clustering for Large Data without Recalculating Cluster Center -- Chapter 7. Supervised Nested Algorithm for Classification based on K-means -- Chapter 8. Using Classification of Regions Based on the Complexity of the Global Progress Indices for Supporting Development in Competitiveness -- Chapter 9. Estimation Methods Based on Weighting Clusters -- Chapter 10. Five Strategies for Accommodating Overdispersion in Simple Correspondence Analysis -- Chapter 11. From Joint Graphical Display to Bi-Modal Cluste
This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields,

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