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90
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ICML
2009
IEEE
16 years 1 months ago
Domain adaptation from multiple sources via auxiliary classifiers
We propose a multiple source domain adaptation method, referred to as Domain Adaptation Machine (DAM), to learn a robust decision function (referred to as target classifier) for l...
Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua
80
Voted
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
15 years 4 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
133
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ECML
1991
Springer
15 years 4 months ago
Semi-Naive Bayesian Classifier
1 A novel semi-naive Bayesian classifier is introduced that is particularly suitable to data with many attributes. The naive Bayesian classifier is taken as a starting point and co...
Igor Kononenko
114
Voted
JMLR
2010
102views more  JMLR 2010»
14 years 7 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
123
Voted
ML
2008
ACM
222views Machine Learning» more  ML 2008»
15 years 19 days ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg