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- Anil K. Jain, Robert P. W. Duin, Jianchang Mao
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2000

ÐThe primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques and methods imported from statistical learning theory… (More)

- Josef Kittler, Mohamad Hatef, Robert P. W. Duin, Jiri Matas
- IEEE Trans. Pattern Anal. Mach. Intell.
- 1998

We develop a common theoretical framework for combining classifiers which use distinct pattern representations and show that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision. An experimental comparison of various classifier combination schemes… (More)

- David M. J. Tax, Robert P. W. Duin
- Machine Learning
- 2004

Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier. It obtains a spherically… (More)

- David M. J. Tax, Robert P. W. Duin
- Pattern Recognition Letters
- 1999

This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors describing the… (More)

- Marco Loog, Robert P. W. Duin
- IEEE Transactions on Pattern Analysis and Machine…
- 2004

We propose an eigenvector-based heteroscedastic linear dimension reduction (LDR) technique for multiclass data. The technique is based on a heteroscedastic two-class technique which utilizes the so-called Chernoff criterion, and successfully extends the well-known linear discriminant analysis (LDA). The latter, which is based on the Fisher criterion, is… (More)

- Ludmila I. Kuncheva, James C. Bezdek, Robert P. W. Duin
- Pattern Recognition
- 2001

Multiple classifier fusion may generate more accurate classification than each of the constituent classifiers. Fusion is often based on fixed combination rules like the product and average. Only under strict probabilistic conditions can these rules be justified. We present here a simple rule for adapting the class combiner to the application. c decision… (More)

- Marco Loog, Robert P. W. Duin, Reinhold Häb-Umbach
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2001

ÐWe derive a class of computationally inexpensive linear dimension reduction criteria by introducing a weighted variant of the well-known K-class Fisher criterion associated with linear discriminant analysis (LDA). It can be seen that LDA weights contributions of individual class pairs according to the Euclidian distance of the respective class means. We… (More)

- Elzbieta Pekalska, Pavel Paclík, Robert P. W. Duin
- Journal of Machine Learning Research
- 2001

Usually, objects to be classified are represented by features. In this paper, we discuss an alternative object representation based on dissimilarity values. If such distances separate the classes well, the nearest neighbor method offers a good solution. However, dissimilarities used in practice are usually far from ideal and the performance of the nearest… (More)

- R P W Duin
- 1995

An introduction into the setup, definitions and use of PRTools is given. Readers are assumed to be familiar with Matlab and should have a basic understanding of field of statistical pattern recognition. The Netherlands-2

- Elzbieta Pekalska, Robert P. W. Duin
- Series in Machine Perception and Artificial…
- 2005