Iterative Boolean combination of classifiers in the ROC space: an application to anomaly detection with HMMs
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Publication:975181
DOI10.1016/j.patcog.2010.03.006zbMath1213.68533OpenAlexW2098373434MaRDI QIDQ975181
Ali Miri, Robert Sabourin, Wael Khreich, Eric Granger
Publication date: 8 June 2010
Published in: Pattern Recognition (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.patcog.2010.03.006
hidden Markov modelsanomaly detectionreceiver operating characteristicscombination of classifierscomputer and network securitylimited and imbalanced data
Related Items (7)
Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines ⋮ An online AUC formulation for binary classification ⋮ ROC curves for regression ⋮ Iterative Boolean combination of classifiers in the ROC space: an application to anomaly detection with HMMs ⋮ A probabilistic model of classifier competence for dynamic ensemble selection ⋮ CCR: a combined cleaning and resampling algorithm for imbalanced data classification ⋮ IRUSRT: A Novel Imbalanced Learning Technique by Combining Inverse Random Under Sampling and Random Tree
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