Statistical learning of complex data [Documento eletrónico] / edited by Francesca Greselin ... [et al.]
Language: eng.Country: Switzerland, Swiss Confederation.Publication: Cham : Springer International Publishing, Springer, 2019Description: XIII, 201 p. : il.ISBN: 978-3-030-21140-0.Series: Studies in Classification Data Analysis and Knowledge OrganizationSubject - Topical Name: Statistics | Mathematical statistics -- Data processing | Data mining | Quantitative research Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|
E-Books | Biblioteca NOVA FCT Online | Não Ficção | QA276.SPR FCT (Browse shelf(Opens below)) | 1 | Available | 95806 |
Browsing Biblioteca NOVA FCT shelves, Shelving location: Online, Collection: Não Ficção Close shelf browser (Hides shelf browser)
QA276.SPR FCT Stochastic comparisons with applications, in order statistics and spacings | QA276.SPR FCT Handbook of cognitive mathematics | QA276.SPR FCT Expository moments for pseudo distributions | QA276.SPR FCT Statistical learning of complex data | QA276.SPR FCT An introduction to algebraic statistics with tensors | QA276.SPR FCT Computational methods to examine team communication, when and how to change the conversation | QA276.SPR FCT Census 2020, understanding the issues |
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.
There are no comments on this title.