Titlebook: Rule Based Systems for Big Data; A Machine Learning A Han Liu,Alexander Gegov,Mihaela Cocea Book 2016 Springer International Publishing Swi

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2197-6503 sentation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems. .978-3-319-37027-9978-3-319-23696-4Series ISSN 2197-6503 Series E-ISSN 2197-6511

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https://doi.org/10.1007/978-3-319-23696-4Big Data; Computational Complexity; Data Mining; Ensemble Learning; Expert Systems; If-Then Rules; Interpr

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Theoretical Preliminaries,As mentioned in Chap. ., some fundamental concepts strongly relate to rule based systems and machine learning, including discrete mathematics, statistics, if-then rules, algorithms, logic and statistical measures of rule quality.

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Case Studies,This chapter introduces three case studies of big data. In particular, the methods and techniques introduced in Chaps. ., ., . and . are evaluated through theoretical analysis and empirical validation using large data sets in terms of accuracy, efficiency and interpretability.

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