Outlier detection with one-class classifiers from ML and KDD

J.H.M. Janssens, I. Flesch, E.O. Postma

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Abstract

    Experimental results show that LOF and SVDD are the two best-performing methods. It is concluded that both fields offer outlier-detection methods that are competitive in performance and that bridging the gap between both fields may facilitate the development of outlier-detection methods.
    Original languageEnglish
    Title of host publicationProceedings of the Eight International Conference on Machine Learning and Applications
    EditorsA. Wani, M. Kantardzic, V. Palade, L. Kurgan, Y. Qi
    Place of PublicationMiami, FL, USA
    PublisherICMLA
    Pages147-153
    Publication statusPublished - 2009

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    Cite this

    Janssens, J. H. M., Flesch, I., & Postma, E. O. (2009). Outlier detection with one-class classifiers from ML and KDD. In A. Wani, M. Kantardzic, V. Palade, L. Kurgan, & Y. Qi (Eds.), Proceedings of the Eight International Conference on Machine Learning and Applications (pp. 147-153). Miami, FL, USA: ICMLA.
    Janssens, J.H.M. ; Flesch, I. ; Postma, E.O. / Outlier detection with one-class classifiers from ML and KDD. Proceedings of the Eight International Conference on Machine Learning and Applications. editor / A. Wani ; M. Kantardzic ; V. Palade ; L. Kurgan ; Y. Qi. Miami, FL, USA : ICMLA, 2009. pp. 147-153
    @inproceedings{9da05e1f1f9b4cab96d58e5ea952d918,
    title = "Outlier detection with one-class classifiers from ML and KDD",
    abstract = "Experimental results show that LOF and SVDD are the two best-performing methods. It is concluded that both fields offer outlier-detection methods that are competitive in performance and that bridging the gap between both fields may facilitate the development of outlier-detection methods.",
    author = "J.H.M. Janssens and I. Flesch and E.O. Postma",
    year = "2009",
    language = "English",
    pages = "147--153",
    editor = "A. Wani and M. Kantardzic and V. Palade and L. Kurgan and Y. Qi",
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    Janssens, JHM, Flesch, I & Postma, EO 2009, Outlier detection with one-class classifiers from ML and KDD. in A Wani, M Kantardzic, V Palade, L Kurgan & Y Qi (eds), Proceedings of the Eight International Conference on Machine Learning and Applications. ICMLA, Miami, FL, USA, pp. 147-153.

    Outlier detection with one-class classifiers from ML and KDD. / Janssens, J.H.M.; Flesch, I.; Postma, E.O.

    Proceedings of the Eight International Conference on Machine Learning and Applications. ed. / A. Wani; M. Kantardzic; V. Palade; L. Kurgan; Y. Qi. Miami, FL, USA : ICMLA, 2009. p. 147-153.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    AU - Janssens, J.H.M.

    AU - Flesch, I.

    AU - Postma, E.O.

    PY - 2009

    Y1 - 2009

    N2 - Experimental results show that LOF and SVDD are the two best-performing methods. It is concluded that both fields offer outlier-detection methods that are competitive in performance and that bridging the gap between both fields may facilitate the development of outlier-detection methods.

    AB - Experimental results show that LOF and SVDD are the two best-performing methods. It is concluded that both fields offer outlier-detection methods that are competitive in performance and that bridging the gap between both fields may facilitate the development of outlier-detection methods.

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    EP - 153

    BT - Proceedings of the Eight International Conference on Machine Learning and Applications

    A2 - Wani, A.

    A2 - Kantardzic, M.

    A2 - Palade, V.

    A2 - Kurgan, L.

    A2 - Qi, Y.

    PB - ICMLA

    CY - Miami, FL, USA

    ER -

    Janssens JHM, Flesch I, Postma EO. Outlier detection with one-class classifiers from ML and KDD. In Wani A, Kantardzic M, Palade V, Kurgan L, Qi Y, editors, Proceedings of the Eight International Conference on Machine Learning and Applications. Miami, FL, USA: ICMLA. 2009. p. 147-153