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» Methods for Dynamic Classifier Selection
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DAWAK
2008
Springer
13 years 9 months ago
Selective Pre-processing of Imbalanced Data for Improving Classification Performance
In this paper we discuss problems of constructing classifiers from imbalanced data. We describe a new approach to selective preprocessing of imbalanced data which combines local ov...
Jerzy Stefanowski, Szymon Wilk
SMC
2007
IEEE
156views Control Systems» more  SMC 2007»
14 years 1 months ago
Dynamic fusion of classifiers for fault diagnosis
—This paper considers the problem of temporally fusing classifier outputs to improve the overall diagnostic classification accuracy in safety-critical systems. Here, we discuss d...
Satnam Singh, Kihoon Choi, Anuradha Kodali, Krishn...
FLAIRS
2008
13 years 10 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
ISI
2005
Springer
14 years 1 months ago
Selective Fusion for Speaker Verification in Surveillance
This paper presents an improved speaker verification technique that is especially appropriate for surveillance scenarios. The main idea is a metalearning scheme aimed at improving ...
Yosef A. Solewicz, Moshe Koppel
ICFHR
2010
151views Biometrics» more  ICFHR 2010»
13 years 2 months ago
Error Reduction by Confusing Characters Discrimination for Online Handwritten Japanese Character Recognition
To reduce the classification errors of online handwritten Japanese character recognition, we propose a method for confusing characters discrimination with little additional costs....
Xiang-Dong Zhou, Da-Han Wang, Masaki Nakagawa, Che...