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ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
15 years 9 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 7 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»
15 years 8 days 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....
ECLIPSE
2007
ACM
15 years 9 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 5 months 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