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» Multiclass relevance vector machines: sparsity and accuracy
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ECML
2006
Springer
13 years 11 months ago
Evaluating Feature Selection for SVMs in High Dimensions
We perform a systematic evaluation of feature selection (FS) methods for support vector machines (SVMs) using simulated high-dimensional data (up to 5000 dimensions). Several findi...
Roland Nilsson, José M. Peña, Johan ...
ICML
2004
IEEE
14 years 8 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
FLAIRS
2008
13 years 9 months ago
On Using SVM and Kolmogorov Complexity for Spam Filtering
As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult t...
Sihem Belabbes, Gilles Richard
DAGM
2010
Springer
13 years 8 months ago
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma
Abstract. We consider an automated processing pipeline for tissue micro array analysis (TMA) of renal cell carcinoma. It consists of several consecutive tasks, which can be mapped ...
Peter J. Schüffler, Thomas J. Fuchs, Cheng So...
BMCBI
2005
117views more  BMCBI 2005»
13 years 7 months ago
An SVM-based system for predicting protein subnuclear localizations
Background: The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computatio...
Zhengdeng Lei, Yang Dai