Algorithms in Machine Learning Paradigms (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.