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.
Publisher: Springer Verlag, Singapore
Number of pages: 195
Weight: 454 g
Dimensions: 235 x 155 mm
Edition: 1st ed. 2020
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