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MCS
2002
Springer
13 years 11 months ago
New Measure of Classifier Dependency in Multiple Classifier Systems
Abstract. Recent findings in the domain of combining classifiers provide a surprising revision of the usefulness of diversity for modelling combined performance. Although there is ...
Dymitr Ruta, Bogdan Gabrys
MCS
2002
Springer
13 years 11 months ago
An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems
In this paper, an experimental comparison between fixed and trained fusion rules for multimodal personal identity verification is reported. We focused on the behaviour of the consi...
Fabio Roli, Josef Kittler, Giorgio Fumera, Daniele...
MCS
2002
Springer
13 years 11 months ago
Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers
So far few theoretical works investigated the conditions under which specific fusion rules can work well, and a unifying framework for comparing rules of different complexity is cl...
Fabio Roli, Giorgio Fumera
MCS
2002
Springer
13 years 11 months ago
A Discussion on the Classifier Projection Space for Classifier Combining
In classifier combining, one tries to fuse the information that is given by a set of base classifiers. In such a process, one of the difficulties is how to deal with the variabilit...
Elzbieta Pekalska, Robert P. W. Duin, Marina Skuri...
MCS
2002
Springer
13 years 11 months ago
Multiclassifier Systems: Back to the Future
Abstract. While a variety of multiple classifier systems have been studied since at least the late 1950's, this area came alive in the 90's with significant theoretical a...
Joydeep Ghosh
MCS
2002
Springer
13 years 11 months ago
On Combining One-Class Classifiers for Image Database Retrieval
Abstract. In image retrieval systems, images can be represented by single feature vectors or by clouds of points. A cloud of points offers a more flexible description but suffers f...
Carmen Lai, David M. J. Tax, Robert P. W. Duin, El...
MCS
2002
Springer
13 years 11 months ago
Forward and Backward Selection in Regression Hybrid Network
Abstract. We introduce a Forward Backward and Model Selection algorithm (FBMS) for constructing a hybrid regression network of radial and perceptron hidden units. The algorithm det...
Shimon Cohen, Nathan Intrator
MCS
2002
Springer
13 years 11 months ago
Distributed Pasting of Small Votes
Bagging and boosting are two popular ensemble methods that achieve better accuracy than a single classifier. These techniques have limitations on massive datasets, as the size of t...
Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowye...
MCS
2002
Springer
13 years 11 months ago
Highlighting Hard Patterns via AdaBoost Weights Evolution
Bruno Caprile, Cesare Furlanello, Stefano Merler