Statistical Learning of Complex Data (Paperback, 1st ed. 2019)

This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. 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 of data analysis and classification. It gathers selected and peer-reviewed contributions presented at the 11th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), held in Milan, Italy, on September 13-15, 2017.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Classification, Data Analysis, and Knowledge Organization
Release date:	September 2019
First published:	2019
Editors:	Francesca Greselin • Laura Deldossi • Luca Bagnato • Maurizio Vichi
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	201
Edition:	1st ed. 2019
ISBN-13:	978-3-03-021139-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	3-03-021139-8
Barcode:	9783030211394

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