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PRL
2002
95views more  PRL 2002»
13 years 4 months ago
Dissimilarity representations allow for building good classifiers
In this paper, a classification task on dissimilarity representations is considered. A traditional way to discriminate between objects represented by dissimilarities is the neares...
Elzbieta Pekalska, Robert P. W. Duin
MCS
2010
Springer
13 years 6 months ago
Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems
Selecting a set of good and diverse base classifiers is essential for building multiple classifier systems. However, almost all commonly used procedures for selecting such base cla...
Wan-Jui Lee, Robert P. W. Duin, Horst Bunke
ICML
2007
IEEE
14 years 5 months ago
Learning to combine distances for complex representations
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
ICML
2007
IEEE
14 years 5 months ago
On learning with dissimilarity functions
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Liwei Wang, Cheng Yang, Jufu Feng
CIARP
2007
Springer
13 years 11 months ago
Generalizing Dissimilarity Representations Using Feature Lines
A crucial issue in dissimilarity-based classification is the choice of the representation set. In the small sample case, classifiers capable of a good generalization and the inje...
Mauricio Orozco-Alzate, Robert P. W. Duin, C&eacut...