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Algorithms in Machine Learning Paradigms (2020)

Contributor(s): Mandal, Jyotsna Kumar (Editor), Mukhopadhyay, Somnath (Editor), Dutta, Paramartha (Editor), Dasgupta, Kousik (Editor)

ISBN: 9789811510434

Publisher: Springer

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Pub Date: January 4, 2021

Dewey: 006.31

Lexile Code: 0000

Features: Illustrated

Target Age Group: NA to NA

Physical Info: 0.44" H x 9.21" L x 6.14" W ( 0.66 lbs) 195 pages

Series: Studies in Computational Intelligence

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Description:

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.


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