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» Hebbian Learning of Bayes Optimal Decisions
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ICML
2010
IEEE
13 years 6 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
13 years 11 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
MCS
2005
Springer
13 years 11 months ago
Ensemble Confidence Estimates Posterior Probability
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
JMLR
2010
125views more  JMLR 2010»
13 years 14 days ago
Variational methods for Reinforcement Learning
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Thomas Furmston, David Barber
LCN
2006
IEEE
13 years 11 months ago
Training on multiple sub-flows to optimise the use of Machine Learning classifiers in real-world IP networks
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...
Thuy T. T. Nguyen, Grenville J. Armitage