TY  - GEN
T1  - Dynamic fuzzy machine learning
A1  - Li, Fanzhang
A1  - Zhang, Li
A1  - Zhang, Zhao
LA  - English
PP  - Berlin
PB  - De Gruyter
YR  - 2018
UL  - https://ebooks.jgu.edu.in/Record/ebsco_acadsubs_on1020026051
AB  - 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.
OP  - 338
CN  - Q325.5
SN  - 9783110518757
SN  - 3110518759
SN  - 3110518708
SN  - 9783110518702
SN  - 9783110520651
SN  - 3110520656
KW  - Machine learning.
KW  - Fuzzy logic.
KW  - Apprentissage automatique.
KW  - Logique floue.
KW  - COMPUTERS : General.
KW  - Fuzzy logic
KW  - Machine learning
ER  -