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198
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DAGM
2006
Springer
15 years 10 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
184
Voted
JIFS
2002
107views more  JIFS 2002»
15 years 6 months ago
Model selection via Genetic Algorithms for RBF networks
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Estefane G. M. de Lacerda, André Carlos Pon...
156
Voted
ICPR
2004
IEEE
16 years 8 months ago
Efficient Model Selection for Kernel Logistic Regression
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
Gavin C. Cawley, Nicola L. C. Talbot
ICML
2008
IEEE
16 years 7 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...
212
Voted
SIGIR
2002
ACM
15 years 6 months ago
Document clustering with cluster refinement and model selection capabilities
In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clus...
Xin Liu, Yihong Gong, Wei Xu, Shenghuo Zhu