Titlebook: Applications of Supervised and Unsupervised Ensemble Methods; Oleg Okun,Giorgio Valentini Book 2009 Springer-Verlag Berlin Heidelberg 2009

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Verifiable Ensembles of Low-Dimensional Submodels for Multi-class Problems with Imbalanced Misclasse ensembles of binary classifiers were developed with the objective of providing interpretable submodels s for use in safety-related application domains. The ensembles assume highly imbalanced misclassification costs between the two classes. The extension to multi-class problems is not straightforwa

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Integrating Liknon Feature Selection and Committee Training,Liknon feature selection method is integrated into the training of a committee of classifiers via external K-fold crossvalidation with an inner loop. In problems, characterized by nonlinear class separation, the Liknon-selected feature profiles, optimal for linear class separation, also identify the

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Oleg Okun,Giorgio ValentiniPresents recent developments of Supervised and Unsupervised Ensemble Methods and Their Applications.Extended contributions from SUEMA 2008 workshop and more

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Applications of Supervised and Unsupervised Ensemble Methods978-3-642-03999-7Series ISSN 1860-949X Series E-ISSN 1860-9503

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S. Geronimi,V. Abadie,N. Beckeruracy. MCSs are currently used in several kinds of applications, among which security applications like biometric identity recognition, intrusion detection in computer networks and spam filtering. However security systems operate in . against intelligent adversaries who try to evade them, and are th

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Wolfgang Bernhart,Marc Winterhoffll companies and large public or private institutions feel that spam has weakened the reliability and effectiveness of email as an efficient tool for communicating. To establish simple, fast and effective countermeasures against spam attacks is a necessary strategy of a modern mailing management sys