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» Optimizing F-Measure with Support Vector Machines
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JCP
2006
78views more  JCP 2006»
13 years 7 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
COLT
2005
Springer
14 years 1 months ago
Learning Convex Combinations of Continuously Parameterized Basic Kernels
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
ESANN
2004
13 years 9 months ago
Evolutionary tuning of multiple SVM parameters
The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
Frauke Friedrichs, Christian Igel
ESA
2010
Springer
227views Algorithms» more  ESA 2010»
13 years 8 months ago
Approximating Parameterized Convex Optimization Problems
We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an -approximat...
Joachim Giesen, Martin Jaggi, Sören Laue
ICML
2003
IEEE
14 years 8 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims