Algorithms in Machine Learning Paradigms

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

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eText | 3 January 2020

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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.