Introduces rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, and neural networks for a holistic understanding
Discusses preprocessing techniques to ensure effective data mining results
Includes numerous illustrative examples and experimental findings for clarity
Extensive bibliographies in each chapter support further research
Applicable to senior undergraduates, graduates, and professionals in computer and information sciences
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The Springer International Series in Engineering and Computer Science Data Mining Methods for Knowledge Discovery Krzysztof J. Cios | Witold Pedrycz | Roman W. Swiniarski Computers / Database Administration & Management Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently us