In this paper we present a new method for fusing classifiers output for problems with a number of classes M > 2. We extend the well-known Behavior Knowledge Space method with a...
Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
A biometric system produces a matching score representing the degree of similarity of the input with the set of templates for that user. If the score is greater than a prefixed th...
The strength of classifier combination lies either in a suitable averaging over multiple experts/sources or in a beneficial integration of complementary approaches. In this paper...
Manuele Bicego, Elzbieta Pekalska, Robert P. W. Du...
In this paper we present a fusion technique for Support Vector Machine (SVM) scores, obtained after a dimension reduction with Bilateralprojection-based Two-Dimensional Principal C...
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Abstract. This paper investigates the use of diverse data fusion methods to improve the performance of the passage retrieval component in a question answering system. Our results o...