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» Applying Support Vector Machines to Imbalanced Datasets
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HIS
2008
13 years 9 months ago
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
Hernán Ahumada, Guillermo L. Grinblat, Luca...
AAAI
2006
13 years 9 months ago
Closest Pairs Data Selection for Support Vector Machines
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
Chaofan Sun
KSEM
2009
Springer
14 years 2 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
BMCBI
2011
12 years 11 months ago
Conotoxin Protein Classification Using Free Scores of Words and Support Vector Machines
Background: Conotoxin has been proven to be effective in drug design and could be used to treat various disorders such as schizophrenia, neuromuscular disorders and chronic pain. ...
Nazar Zaki, Stefan Wolfsheimer, Grégory Nue...
BMCBI
2010
151views more  BMCBI 2010»
13 years 7 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou