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» Evaluating learning algorithms and classifiers
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IJIT
2004
15 years 5 months ago
Evaluation of Algorithms for Sequential Decision in Biosonar Target Classification
A sequential decision problem, based on the task of identifying the species of trees given acoustic echo data collected from them, is considered with well-known stochastic classifi...
Turgay Temel, John Hallam
CVPR
2010
IEEE
15 years 8 months ago
On the design of robust classifiers for computer vision
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Vijay Mah...
MCS
2007
Springer
15 years 10 months ago
An Ensemble Approach for Incremental Learning in Nonstationary Environments
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...
Michael Muhlbaier, Robi Polikar
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 5 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
JMLR
2002
144views more  JMLR 2002»
15 years 3 months ago
Round Robin Classification
In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...
Johannes Fürnkranz