Algorithms in Machine Learning Paradigms (Paperback, 1st ed. 2020)

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Studies in Computational Intelligence, 870
Release date:	2021
First published:	2020
Editors:	Jyotsna Kumar Mandal • Somnath Mukhopadhyay • Paramartha Dutta • Kousik Dasgupta
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	195
Edition:	1st ed. 2020
ISBN-13:	978-981-15-1043-4
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	981-15-1043-1
Barcode:	9789811510434

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