Titlebook: Emerging Paradigms in Machine Learning; Sheela Ramanna,Lakhmi C Jain,Robert J. Howlett Book 2013 Springer-Verlag Berlin Heidelberg 2013 Em

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2190-3018 lding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.? ?.978-3-642-43574-4978-3-642-28699-5Series ISSN 2190-3018 Series E-ISSN 2190-3026

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Sheela Ramanna,Lakhmi C Jain,Robert J. HowlettState of the art of emerging paradigms in machine learning including some real world applications.Latest research in machine learning and biologically-based techniques for the design and implementatio

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https://doi.org/10.1007/978-3-642-28699-5Emerging paradigms; Emerging paradigms; Intelligent systems; Intelligent systems; Machine learning; Machi

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,Enige Grondlijnen van Abélard’s Theologie,esian Learning, Decision Trees, Granular Computing, Fuzzy and Rough Sets, Inductive Logic Programming, Reinforcement Learning, Neural Networks and Support Vector Machines. In addition, challenges in ML such as imbalanced data, perceptual computing, and pattern recognition of data which is episodic as well as temporal are also highlighted.

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Emerging Paradigms in Machine Learning: An Introduction,esian Learning, Decision Trees, Granular Computing, Fuzzy and Rough Sets, Inductive Logic Programming, Reinforcement Learning, Neural Networks and Support Vector Machines. In addition, challenges in ML such as imbalanced data, perceptual computing, and pattern recognition of data which is episodic as well as temporal are also highlighted.

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