Recent Trends and Future Challenges in Learning from Data
Language: English
Published by Springer, Springer International Publishing Aug 2024, 2024
- Softcover
- New
Seller: Wegmann1855, Zwiesel, GermanyWegmann1855
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Neuware -This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: ¿Avoiding drowning in the data: recent trends and future challenges in learning from datä. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance. …
Seller Inventory # 9783031544675
- Title
- Recent Trends and Future Challenges in Learning from Data
- Author
- Cristina Davino
- Publisher
- Springer, Springer International Publishing Aug 2024
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3031544676
- ISBN 13
- 9783031544675
- Item weight
- 260 grams
- Dimensions
- 235x155x10 mm
This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: “Avoiding drowning in the data: recent trends and future challenges in learning from data”. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.
"Synopsis" may belong to another edition of this title.
About the Author
Cristina Davino is an Associate Professor in Statistics at the University of Naples Federico II, Italy. Her fields of interest and areas of expertise are multidimensional data analysis, data mining, quantile regression, statistical surveys, quality of life assessment, evaluation of university education processes, construction and validation of composite indicators and analysis of learning processes. She has been involved in many research projects whose results have been disseminated in international journals and conferences.
Francesco Palumbo is a Professor of Statistics at Federico II University of Naples, Italy. He teaches Statistics and Psychometric Statistics in basic and advanced courses. He is the Editor-in-Chief of the Italian Journal of Applied Statistics and an Associate Editor of Computational Statistics. He has collaborated on numerous European projects and has participated in and coordinated several national research projects. His main research interests are in classification and data analysis.
Adalbert Wilhelm holds a Professorship in Statistics at Constructor University, Bremen, Germany. He is also the Vice Dean of the Bremen International Graduate School of Social Sciences (BIGSSS). His main research is on statistical visualization, exploratory data analysis and data mining and his recent work addresses questions of digitalization and big data applied to a broad range of disciplines such as economics, business administration, political science, sociology and psychology.
Hans A. Kestler is currently a Professor and the Head of the Institute of Medical Systems Biology and the Core Unit Bioinformatics within the Faculties of Computer Science and Medicine, Ulm University, Germany. He is also an Associated Group Leader with the Leibniz Institute on Aging, Jena. He has published more than 330 articles in journals, books, and conferences. His research interests include methodological foundations of pattern recognition, bioinformatics, molecular systems biology, and digital health.
"About the title" may belong to another edition of this title.
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