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 Название: Advances in Data Science: Symbolic, Complex, and Network Data
Автор: Edwin Diday, Rong Guan, Gilbert Saporta, Huiwen Wang
Издательство: Wiley-ISTE
Год: 2020
Формат: PDF
Страниц: 258
Размер: 11 Mb
Язык: English
Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. Special kinds of data (symbolic, network, complex, compositional) are increasingly frequent in data science. These data require specific methodologies, but there is a lack of reference work in this field.
Advances in Data Science fills this gap. It presents a collection of up-to-date contributions by eminent scholars following two international workshops held in Beijing and Paris. The 10 chapters are organized into four parts: Symbolic Data, Complex Data, Network Data and Clustering. They include fundamental contributions, as well as applications to several domains, including business and the social sciences.
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Автор: Maurix 16-01-2020, 14:13 | Напечатать
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Advances in Data Science: Symbolic, Complex, and Network Data 
