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» Feature selection for linear support vector machines
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SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
14 years 5 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
CICLING
2010
Springer
13 years 2 months ago
An Empirical Study on the Feature's Type Effect on the Automatic Classification of Arabic Documents
The Arabic language is a highly flexional and morphologically very rich language. It presents serious challenges to the automatic classification of documents, one of which is deter...
Saeed Raheel, Joseph Dichy
LREC
2008
160views Education» more  LREC 2008»
13 years 9 months ago
Automatic Extraction of Textual Elements from News Web Pages
In this paper we present an algorithm for automatic extraction of textual elements, namely titles and full text, associated with news stories in news web pages. We propose a super...
Hossam Ibrahim, Kareem Darwish, Abdel-Rahim Madany
ICML
2006
IEEE
14 years 8 months ago
Optimal kernel selection in Kernel Fisher discriminant analysis
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
ICIP
2003
IEEE
14 years 1 months ago
ICA and Gabor representation for facial expression recognition
Two hybrid systems for classifying seven categories of human facial expression are proposed. The £rst system combines independent component analysis (ICA) and support vector mach...
Ioan Buciu, Constantine Kotropoulos, Ioannis Pitas