Classification, (Big) Data Analysis and Statistical Learning

• Corporate Author: SpringerLink (Online service)
• Other Authors: Mola, Francesco (Editor, http://id.loc.gov/vocabulary/relators/edt), Conversano, Claudio (Editor, http://id.loc.gov/vocabulary/relators/edt), Vichi, Maurizio (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Studies in Classification, Data Analysis, and Knowledge Organization,
• Subjects: Statistics .; Data mining.; Big data.; Statistical Theory and Methods.; Statistics and Computing/Statistics Programs.; Statistics for Business, Management, Economics, Finance, Insurance.; Data Mining and Knowledge Discovery.; Big Data.
• Physical Description: XVI, 242 p. 65 illus., 21 illus. in color. online resource.
• ISBN: 9783319557083
• ISSN: 1431-8814
• DOI: 10.1007/978-3-319-55708-3

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8-10, 2015.