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» Methods for Dynamic Classifier Selection
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DAWAK
2008
Springer
15 years 6 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»
15 years 10 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
15 years 6 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
15 years 10 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
156
Voted
ICFHR
2010
151views Biometrics» more  ICFHR 2010»
14 years 11 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...