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» Support Vector Machines for Multi-class Classification
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ICML
2004
IEEE
14 years 9 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
ICML
2000
IEEE
14 years 9 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner
ECML
2006
Springer
14 years 14 days ago
Fisher Kernels for Relational Data
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Uwe Dick, Kristian Kersting
ICDIM
2008
IEEE
14 years 3 months ago
Unsupervised key-phrases extraction from scientific papers using domain and linguistic knowledge
The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement ...
Mikalai Krapivin, Maurizio Marchese, Andrei Yadran...
BMCBI
2007
178views more  BMCBI 2007»
13 years 8 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat