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94
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ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
15 years 4 months ago
Arbiter Meta-Learning with Dynamic Selection of Classifiers and Its Experimental Investigation
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Alexey Tsymbal, Seppo Puuronen, Vagan Y. Terziyan
AUSAI
2008
Springer
15 years 2 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
JMLR
2010
172views more  JMLR 2010»
14 years 7 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
120
Voted
ECLIPSE
2007
ACM
15 years 4 months ago
Predicting buggy changes inside an integrated development environment
We present a tool that predicts whether the software under development inside an IDE has a bug. An IDE plugin performs this prediction, using the Change Classification technique t...
Janaki T. Madhavan, E. James Whitehead Jr.
PR
2006
111views more  PR 2006»
15 years 14 days ago
An adaptive error penalization method for training an efficient and generalized SVM
A novel training method has been proposed for increasing efficiency and generalization of support vector machine (SVM). The efficiency of SVM in classification is directly determi...
Yiqiang Zhan, Dinggang Shen