Overview
- Presents the latest advances in data analysis, classification and clustering
- Includes contributions on classification methods for high-dimensional data
- Fosters further methodological and applied research in data science
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
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Table of contents (26 papers)
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Front Matter
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Classification Methods for High Dimensional Data
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Front Matter
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Clustering Methods and Applications
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Front Matter
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Multivariate Methods and Applications
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Front Matter
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Keywords
About this book
This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.
Editors and Affiliations
About the editors
Francesco Palumbo has been a full Professor of Statistics at the University of Naples Federico II since 2009. Associate professor and Full Professor at University of Macerata from 1996 to 2009. Master’s degree summa cum laude in Business and Economics; Ph.D. in Computational Statistics, University Federico II in Naples, Italy; Post-Doctoral Fellowship, University Federico II in Naples, Italy. He currently teaches Statistics and Psychometrics in intermediate and advanced courses. Associated Editor of Computational Statistics and Italian Journal of Applied Statistics. Scientific Secretary of the IASC (2007-2009), IASC Council Member 2009-2013. President of ClaDAG (Classification and Data Analysis Group of the Italian Statistical Society). Invited speaker at several International conferences on Complex Data and Cluster Analysis. He has been a Visiting Professor at CERAMADE Laboratory Paris Dauphine and at Conservatoire National des Arts et Metiers (Paris).
Angela Montanari has been a full Professor of Statistics at the University of Bologna since 2000. She is currently the Director of the University’s Department of Statistical Sciences “P. Fortunati,”, and a member of the teaching board for the PhD program on “Statistical Sciences”. She is fellow of several international scientific societies, including the International Association for Statistics and Computing and the International Biometric Society. She was President of Cladag from 2007-2009. She is member of the editorial board of the journal Advances in Data Analysis and Classification and of the NSERC Discovery Grant evaluation committee. She is the author or co-author of more than forty international publications.
Maurizio Vichi is full Professor of Statistics and Head of the Department of Statistical Sciences at Sapienza University of Rome. He is President of the Federation of European National Statistical Societies (FENStatS), former President of the Italian Statistical Society, and of the International Federation of Classification Societies (IFCS). He is coordinating editor of the journal Advances in Data Analysis and Classification, Editor of the international book series Classification, Data Analysis and Knowledge Organization, and the series Studies in Theoretical and Applied Statistics, published by Springer. He is a member of ESAC (European Statistical Advisory Committee of European Union). He is author of several papers published in international Journals.
Bibliographic Information
Book Title: Data Science
Book Subtitle: Innovative Developments in Data Analysis and Clustering
Editors: Francesco Palumbo, Angela Montanari, Maurizio Vichi
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-319-55723-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-55722-9Published: 05 July 2017
eBook ISBN: 978-3-319-55723-6Published: 04 July 2017
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XVI, 342
Number of Illustrations: 11 b/w illustrations, 39 illustrations in colour
Topics: Statistical Theory and Methods, Data Mining and Knowledge Discovery, Statistics and Computing/Statistics Programs, Big Data, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Business, Management, Economics, Finance, Insurance