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Titlebook: Machine Learning Paradigms; Applications in Reco Aristomenis S. Lampropoulos,George A. Tsihrintzis Book 2015 Springer International Publish

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978-3-319-38496-2Springer International Publishing Switzerland 2015
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Machine Learning Paradigms978-3-319-19135-5Series ISSN 1868-4394 Series E-ISSN 1868-4408
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The Learning Problem,s distinctive attributes of intelligent behavior. Machine Learning is the study of how to develop algorithms, computer applications, and systems that have the ability to learn and, thus, improve through experience their performance at some tasks. This chapter presents the formalization of the Machine Learning Problem.
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Similarity Measures for Recommendations Based on Objective Feature Subset Selection, users are constructed from . audio signal features by associating different music similarity measures to different users. Specifically, our approach in developing MUSIPER is based on investigating certain subsets in the . feature set and their relation to the . music similarity perception of individuals.
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Aristomenis S. Lampropoulos,George A. TsihrintzisPresents recent applications of Recommender Systems.Intended for both the expert and researcher in the fields of Pattern Recognition, Machine Learning and Recommender Systems, as well as for the gener
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Intelligent Systems Reference Libraryhttp://image.papertrans.cn/m/image/620413.jpg
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neral drive and in its specific features and eventual inner tensions...The chapters of the book are the result of intense discussion in the course of an international conference focused on the title question of this book, and were selected in view of their contribution to this topic. They are cluste
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