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 Seamless Healthcare Monitoring by
Cover of the book Non-equilibrium Phenomena in Confined Soft Matter by
Cover of the book The Philosophy of Quantum Physics by
Cover of the book Filtering and Control of Stochastic Jump Hybrid Systems by
Cover of the book Applying Comparative Effectiveness Data to Medical Decision Making by
Cover of the book Out of the Past by
Cover of the book Geoinformation for Informed Decisions by
Cover of the book Consultation in Neurourology by
Cover of the book Electric Power Engineering Research and Education by
Cover of the book Advances in Mobile Cloud Computing and Big Data in the 5G Era by
Cover of the book Tympanic Membrane Retraction Pocket by
Cover of the book Ethics and Politics of the Built Environment by
Cover of the book Animals and Desire in South African Fiction by
Cover of the book Law, Development and Innovation by
Cover of the book Temporal Points of View 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