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Dynamic Fuzzy Machine Learning eBook

by Li Zhang, Zhao Zhang e Fanzhang Li
language: english
Publisher: De Gruyter, December of 2017 ‧
217,96€
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Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic.

This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Dynamic Fuzzy Machine Learning

by Li Zhang, Zhao Zhang e Fanzhang Li

Property Description
ISBN: 9783110518757
Publisher: De Gruyter
Release Date: December of 2017
Language: English
Format: eBook
File Format and Compatibility:
Categories: eBooks in English > Engineering > General Engineering
eBooks in English > Computing > Other Applications
eBooks in English > Computing > Schedule
EAN: 9783110518757
Acessibilidade: Ver características de acessibilidade indicadas pelo editor