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MCS
2007
Springer
15 years 10 months ago
Classifier Combining Rules Under Independence Assumptions
Classifier combining rules are designed for the fusion of the results from the component classifiers in a multiple classifier system. In this paper, we firstly propose a theoretica...
Shoushan Li, Chengqing Zong
MCS
2007
Springer
15 years 10 months ago
An Experimental Study on Rotation Forest Ensembles
Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...
Ludmila I. Kuncheva, Juan José Rodrí...
MCS
2007
Springer
15 years 10 months ago
Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification
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...
Ángel Serrano, Isaac Martín de Diego...
MCS
2007
Springer
15 years 10 months ago
Group-Induced Vector Spaces
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...
MCS
2007
Springer
15 years 10 months ago
Index Driven Combination of Multiple Biometric Experts for AUC Maximisation
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...
Roberto Tronci, Giorgio Giacinto, Fabio Roli