Classification, (Big) Data Analysis and Statistical Learning

Nonfiction, Science & Nature, Mathematics, Statistics, Computers, Application Software
Cover of the book Classification, (Big) Data Analysis and Statistical Learning by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319557083
Publisher: Springer International Publishing Publication: February 21, 2018
Imprint: Springer Language: English
Author:
ISBN: 9783319557083
Publisher: Springer International Publishing
Publication: February 21, 2018
Imprint: Springer
Language: English

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 Pula (Cagliari), Italy, October 8–10, 2015.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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 Pula (Cagliari), Italy, October 8–10, 2015.

More books from Springer International Publishing

Cover of the book An Introduction to Riemannian Geometry by
Cover of the book Studies in Theoretical and Applied Statistics by
Cover of the book Conceptual Modeling by
Cover of the book Improving Sustainability During Hospital Design and Operation by
Cover of the book Neo-Tribes by
Cover of the book Education and Empire by
Cover of the book Nonequilibrium and Irreversibility by
Cover of the book The Presence of God and the Presence of Persons by
Cover of the book 3D Geoinformation Science by
Cover of the book Perspectives on the U.S.-Mexico Soccer Rivalry by
Cover of the book Luminescence Dating in Archaeology, Anthropology, and Geoarchaeology by
Cover of the book The Kurds in a New Middle East by
Cover of the book Artificial Intelligence and Signal Processing by
Cover of the book Advances in Gender and Cultural Research in Business and Economics by
Cover of the book The Future of Leadership - An Explorative Study into Tomorrow's Leadership Challenges by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy