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» Proximal support vector machine classifiers
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CIDM
2009
IEEE
14 years 2 months ago
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
—  Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
Hamoud I. Aljamaan, Mahmoud O. Elish
PRL
2006
79views more  PRL 2006»
13 years 7 months ago
Multi-class feature selection for texture classification
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
Xue-wen Chen, Xiang-Yan Zeng, Deborah van Alphen
ICSE
2004
IEEE-ACM
14 years 7 months ago
Finding Latent Code Errors via Machine Learning over Program Executions
This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
Yuriy Brun, Michael D. Ernst
KDD
2006
ACM
174views Data Mining» more  KDD 2006»
14 years 8 months ago
Onboard classifiers for science event detection on a remote sensing spacecraft
Typically, data collected by a spacecraft is downlinked to Earth and pre-processed before any analysis is performed. We have developed classifiers that can be used onboard a space...
Ashley Davies, Benjamin Cichy, Dominic Mazzoni, Ng...
CIKM
2008
Springer
13 years 9 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan