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» Optimal feature selection for support vector machines
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OL
2007
103views more  OL 2007»
13 years 7 months ago
Support vector machine via nonlinear rescaling method
In this paper we construct the linear support vector machine (SVM) based on the nonlinear rescaling (NR) methodology (see [9, 11, 10] and references therein). The formulation of t...
Roman A. Polyak, Shen-Shyang Ho, Igor Griva

Publication
265views
14 years 4 months ago
Effective 2D-3D Medical Image Registration using Support Vector Machine
Registration of pre-operative 3D volume dataset and intra-operative 2D images gradually becomes an important technique to assist radiologists in diagnosing complicated diseases. In...
Wenyuan Qi, Lixu Gu
COLING
2002
13 years 7 months ago
Extracting Important Sentences with Support Vector Machines
Extracting sentences that contain important information from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar ...
Tsutomu Hirao, Hideki Isozaki, Eisaku Maeda, Yuji ...
KDD
2005
ACM
117views Data Mining» more  KDD 2005»
14 years 8 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
EOR
2007
101views more  EOR 2007»
13 years 7 months ago
Comprehensible credit scoring models using rule extraction from support vector machines
In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...