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Descrizione libro Condizione: New. Codice articolo ABLIING23Apr0316110144079
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Descrizione libro Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The medical data are usually multidimensional,and is presented by a large number of features. The inclusion of irrelevant, redundant and noisy features in the process model can result in poor predictive accuracy and increased computation. The success of the data mining technique is based on the selection of a small set of highly predictive attributes. Feature selection techniques extract informative features from medical databases to facilitate medical decision making in an effective and efficient way. The feature selection methods discussed, both Wrapper and Filter methods, use feature ranking methods to identify the informative and discriminatory features of the medical datasets, which greatly influence the predictive accuracy of the classifiers. There is a significant improvement in the sensitivity and specificity values which shows that the feature selection indeed improves the discriminating ability of the classifiers. The focus is on aggressive dimensionality reduction with an increase in the prediction accuracy. 120 pp. Englisch. Codice articolo 9783848434329
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Descrizione libro PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9783848434329
Descrizione libro Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The medical data are usually multidimensional,and is presented by a large number of features. The inclusion of irrelevant, redundant and noisy features in the process model can result in poor predictive accuracy and increased computation. The success of the data mining technique is based on the selection of a small set of highly predictive attributes. Feature selection techniques extract informative features from medical databases to facilitate medical decision making in an effective and efficient way. The feature selection methods discussed, both Wrapper and Filter methods, use feature ranking methods to identify the informative and discriminatory features of the medical datasets, which greatly influence the predictive accuracy of the classifiers. There is a significant improvement in the sensitivity and specificity values which shows that the feature selection indeed improves the discriminating ability of the classifiers. The focus is on aggressive dimensionality reduction with an increase in the prediction accuracy. Codice articolo 9783848434329
Descrizione libro Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sarojini B.Dr.B.Sarojini,is an Assistant Professor, Department of Computer Science, Avinashilingam University for Women, Coimbatore, India. Her research interests include Medical Informatics,Web mining & Security. Dr.N.Ram. Codice articolo 5521896