Statistical learning of complex data. Selected papers of the 11th scientific meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), Milan, Italy, September 13–15, 2017. (English) Zbl 1427.62004

Studies in Classification, Data Analysis, and Knowledge Organization. Cham: Springer (ISBN 978-3-030-21139-4/pbk; 978-3-030-21140-0/ebook). xiii, 201 p. (2019).

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Publisher’s description: 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.
The articles of mathematical interest will be reviewed individually.
Indexed articles:
Alfó, Marco; Nieddu, Luciano; Vitiello, Cecilia, Cluster weighted beta regression: a simulation study, 3-11 [Zbl 1436.62234]
Cappozzo, Andrea; Greselin, Francesca, Detecting wine adulterations employing robust mixture of factor analyzers, 13-21 [Zbl 1436.62245]
Fordellone, Mario; Vichi, Maurizio, Simultaneous supervised and unsupervised classification modeling for assessing cluster analysis and improving results interpretability, 23-31 [Zbl 1436.62249]
Rainey, Christopher; Tortora, Cristina; Palumbo, Francesco, A parametric version of probabilistic distance clustering, 33-43 [Zbl 1436.62281]
Ranalli, Monia; Rocci, Roberto, An overview on the URV model-based approach to cluster mixed-type data, 45-53 [Zbl 1436.62282]
Bove, Giuseppe; Ruta, Nicole; Mastandrea, Stefano, Preference analysis of architectural façades by multidimensional scaling and unfolding, 57-64 [Zbl 1436.62359]
Altimari, Ambra; Balzano, Simona; Zezza, Gennaro, Measuring economic vulnerability: a structural equation modeling approach, 95-102 [Zbl 1436.62684]
Ascari, Roberto; Migliorati, Sonia; Ongaro, Andrea, Bayesian inference for a mixture model on the simplex, 103-110 [Zbl 1436.62180]
Vernizzi, Graziano; Nakai, Miki, Weighted optimization with thresholding for complete-case analysis, 143-151 [Zbl 1436.62053]
Musella, Flaminia; Vicard, Paola; Vitale, Vincenzina, Copula grow-shrink algorithm for structural learning, 163-171 [Zbl 1436.62188]
Nicolussi, Federica; Cazzaro, Manuela, Context-specific independencies embedded in chain graph models of type I, 173-180 [Zbl 1436.62211]
Pesce, Elena; Riccomagno, Eva; Wynn, Henry P., Experimental design issues in big data: the question of bias, 193-201 [Zbl 1436.62385]


62-06 Proceedings, conferences, collections, etc. pertaining to statistics
62Hxx Multivariate analysis
62R07 Statistical aspects of big data and data science
68T05 Learning and adaptive systems in artificial intelligence
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