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Fitting mixtures of regression lines with the forward search: application to clustering and outlier detection

This video was recorded at NATO Advanced Study Institute on Mining Massive Data Sets for Security. The forward search is a method for detecting unidentified subsets and masked outliers and for determining their effect on models fitted to the data. This talk describes a semi-automatic approach to outlier detection and clustering through the forward search. We address challenging issues including selection of the number of groups. The performance of the algorithm is shown on several trade data sets relevant for fraud detection problems.

Keywords:: Cluster analysis, videolectures, regression, mixture, outlier detection, ocwc, oec

Disciplines:

Science and Technology / Computer Science / Programming & Programming Languages

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Material Type:: Presentation
Date Added to MERLOT:: February 10, 2015
Date Modified in MERLOT:: February 10, 2015
Authors:: Domenico Perrotta, Joint Research Centre
Andrea Cerioli, Facoltà di Economia, University of Parma
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed, College Lower Division, College Upper Division
Technical Format:: Video

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States