Combining Dissimilarity-Based One-Class Classifiers

We address a one-class classification (OCC) problem aiming at detection of objects that come from a pre-defined target class. Since the non-target class is ill-defined, an effective set of features discriminating between the targets and non-targets is hard to obtain. Alternatively, when raw data are available, dissimilarity representations describing an object by its dissimilarities to a set of target examples can be used.

[1]  Robert P. W. Duin,et al.  One-Class LP Classifiers for Dissimilarity Representations , 2002, NIPS.

[2]  Paul S. Bradley,et al.  Feature Selection via Mathematical Programming , 1997, INFORMS J. Comput..

[3]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[4]  Bernhard Schölkopf,et al.  Estimating the Support of a High-Dimensional Distribution , 2001, Neural Computation.

[5]  N. JARDINE,et al.  A New Approach to Pattern Recognition , 1971, Nature.

[6]  Robert P. W. Duin,et al.  Support Vector Data Description , 2004, Machine Learning.

[7]  Robert P.W. Duin,et al.  PRTools3: A Matlab Toolbox for Pattern Recognition , 2000 .

[8]  G. Wagner,et al.  The topology of the possible: formal spaces underlying patterns of evolutionary change. , 2001, Journal of theoretical biology.

[9]  Azriel Rosenfeld,et al.  Progress in pattern recognition , 1985 .

[10]  Hans-Hermann Bock,et al.  Analysis of Symbolic Data , 2000 .

[11]  Daphna Weinshall,et al.  Classification with Nonmetric Distances: Image Retrieval and Class Representation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  J. Roodenburg,et al.  Autofluorescence characteristics of healthy oral mucosa at different anatomical sites , 2003, Lasers in surgery and medicine.

[13]  Robert P. W. Duin,et al.  A Generalized Kernel Approach to Dissimilarity-based Classification , 2002, J. Mach. Learn. Res..

[14]  Robert P. W. Duin,et al.  Combining One-Class Classifiers , 2001, Multiple Classifier Systems.