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ECML
2004
Springer
15 years 3 months ago
Applying Support Vector Machines to Imbalanced Datasets
Support Vector Machines (SVM) have been extensively studied and have shown remarkable success in many applications. However the success of SVM is very limited when it is applied to...
Rehan Akbani, Stephen Kwek, Nathalie Japkowicz
TR
2010
204views Hardware» more  TR 2010»
14 years 4 months ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
JMLR
2011
110views more  JMLR 2011»
14 years 4 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
DAGM
2004
Springer
15 years 1 months ago
Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features
Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We a...
Matthias Rätsch, Sami Romdhani, Thomas Vetter
ECML
2006
Springer
14 years 11 months ago
Efficient Large Scale Linear Programming Support Vector Machines
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Suvrit Sra