1584 search results - page 105 / 317 » Data selection for support vector machine classifiers |
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
101
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TNN
2010
14 years 4 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
IJBRA
2010
14 years 7 months ago
2010
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
BMCBI
2007
14 years 10 months ago
2007
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
119
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ESANN
2006
14 years 11 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...