Data mining : foundations and practice

This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a scientific discipline, while the practical studies of data mining may lead to new data mining paradigm...

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Détails bibliographiques
Auteur principal: Lin, Tsau Young
Autres auteurs: Xie, Ying (Éditeur intellectuel), Wasilewska, Anita (Éditeur intellectuel), Liau, Churn-Jung (Éditeur intellectuel), Kacprzyk, Janusz, 1947- (Directeur de la publication), Liau, Churn-Jung, 19..- (Directeur de la publication), Lin, Tsau Young, 1937- (Directeur de la publication), Wasilewska, Anita, 19..- (Directeur de la publication), Xie, Ying, 19..- (Directeur de la publication)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2008.
Collection:Studies in Computational Intelligence 118
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Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Data Mining: Foundations and Practice, Texte imprimé, 9783540784876
• Data Mining: Foundations and Practice, Texte imprimé, 9783540870975
• Data Mining: Foundations and Practice, Texte imprimé, 9783642097225
• Data Mining: Foundations and Practice, Texte imprimé, 9783540784876
Description
Résumé:This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a scientific discipline, while the practical studies of data mining may lead to new data mining paradigms and algorithms. The foundational studies contained in this book focus on a broad range of subjects, including conceptual framework of data mining, data preprocessing and data mining as generalization, probability theory perspective on fuzzy systems, rough set methodology on missing values, inexact multiple-grained causal complexes, complexity of the privacy problem, logical framework for template creation and information extraction, classes of association rules, pseudo statistical independence in a contingency table, and role of sample size and determinants in granularity of contingency matrix. The practical studies contained in this book cover different fields of data mining, including rule mining, classification, clustering, text mining, Web mining, data stream mining, time series analysis, privacy preservation mining, fuzzy data mining, ensemble approaches, and kernel based approaches. We believe that the works presented in this book will encourage the study of data mining as a scientific field and spark collaboration among researchers and practitioners
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783540784883
ISSN:1860-9503
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Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017