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Algorithms in Machine Learning Paradigms Hardback - 2020
by Jyotsna Kumar Mandal (Editor); Somnath Mukhopadhyay (Editor); Paramartha Dutta (Editor)
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From the rear cover
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.
Details
- Title Algorithms in Machine Learning Paradigms
- Author Jyotsna Kumar Mandal (Editor); Somnath Mukhopadhyay (Editor); Paramartha Dutta (Editor)
- Binding Hardback
- Pages 195
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2020-01-04
- Illustrated Yes
- Features Illustrated
- ISBN 9789811510403 / 9811510407
- Weight 1.03 lbs (0.47 kg)
- Dimensions 9.21 x 6.14 x 0.5 in (23.39 x 15.60 x 1.27 cm)
- Category Mathematics
- Dewey Decimal Code 006.31
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Algorithms in Machine Learning Paradigms (Studies in Computational Intelligence)
by Mandal, Jyotsna Kumar (Editor) / Mukhopadhyay, Somnath (Editor) / Dutta, Paramartha (Editor) / Dasgupta, Kousik (Editor)
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Algorithms in Machine Learning Paradigms
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