Classification, (Big) Data Analysis and Statistical Learning. 1st ed. 2018

種類:

電子ブック

責任表示:

edited by Francesco Mola, Claudio Conversano, Maurizio Vichi

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2018

著者名:

• Mola, Francesco.
• Conversano, Claudio.
• Vichi, Maurizio.
• SpringerLink (Online service)

シリーズ名:

Studies in Classification, Data Analysis, and Knowledge Organization ;

ISBN:

9783319557083 [3319557084]    

注記:

Rank Properties for Centred Three-way Arrays – C. Albers (Univ. of Groningen) et al -- Principal Component Analysis of Complex Data and Application to Climatology – S. Camiz (La Sapienza Univ. of Rome) et al -- Clustering upper level units in multilevel models for ordinal data – L. Grilli (Univ. of Florence) et al -- A Multilevel Heckman Model To Investigate Financial Assets Among Old People In Europe – O. Paccagnella (univ. of Padua) et al -- Multivariate stochastic downscaling with semicontinuous data – L. Paci (univ. of Bologna) et al -- Motivations and expectations of students’ mobility abroad: a mapping technique – V. Caviezel (Univ. of Bergamo) et al -- Comparing multi-step ahead forecasting functions for time series clustering – M. Corduas (Univ. of Naples Federico II) et al -- Electre Tri-Machine Learning Approach to the Record Linkage – V. Minnetti (La Sapienza Univ. of Rome) et al -- . MCA Based Community Detection – C. Drago (Univ. of Rome Niccolò Cusano) -- Classi fying social roles by network str
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 Pul

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