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.
Explore Algorithms in Machine Learning Paradigms by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta & Kousik Dasgupta on eBooksStore by Arnlweb. Discover book details, reader ratings, reviews, release information, genres, and related digital books available through the iTunes Store.
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