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CIDM
2009
IEEE
15 years 5 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
ICASSP
2011
IEEE
14 years 2 months ago
Fall detection in a smart room by using a fuzzy one class support vector machine and imperfect training data
In this paper, we propose an efficient and robust fall detection system by using a fuzzy one class support vector machine based on video information. Two cameras are used to capt...
Miao Yu, Syed Mohsen Naqvi, Adel Rhuma, Jonathon A...
IWANN
2005
Springer
15 years 4 months ago
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
15 years 4 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
JMLR
2006
150views more  JMLR 2006»
14 years 11 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian