Algorithms in Machine Learning Paradigms

This book gathers studies on algorithms within the machine learning paradigms. It covers a wide range of learning problems and their diverse applications, among them 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.