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To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures.
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Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.
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A comprehensive introduction to statistical methods for data mining and knowledge discovery.
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* Provides a detailed and up-to-date overview on classification and data mining methods. * Focuses on supervised classification algorithms and their applications, including recent research on the combination of classifiers.
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Digital technologies are reshaping every field of social and economic lives, so do they in the world of scientific knowledge. The... Læs mere
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Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates.
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The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the... Læs mere
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Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book... Læs mere
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Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools.... Læs mere