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TNN
2008
133views more  TNN 2008»
13 years 7 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
NIPS
2000
13 years 9 months ago
Kernel Expansions with Unlabeled Examples
Modern classification applications necessitate supplementing the few available labeled examples with unlabeled examples to improve classification performance. We present a new tra...
Martin Szummer, Tommi Jaakkola
COMSIS
2006
156views more  COMSIS 2006»
13 years 7 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
ICDM
2007
IEEE
151views Data Mining» more  ICDM 2007»
13 years 11 months ago
Combining Collective Classification and Link Prediction
The problems of object classification (labeling the nodes of a graph) and link prediction (predicting the links in a graph) have been largely studied independently. Commonly, obje...
Mustafa Bilgic, Galileo Namata, Lise Getoor
AAAI
2007
13 years 10 months ago
Cautious Inference in Collective Classification
Collective classification can significantly improve accuracy by exploiting relationships among instances. Although several collective inference procedures have been reported, they...
Luke McDowell, Kalyan Moy Gupta, David W. Aha