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» Optimal feature selection for support vector machines
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MMM
2005
Springer
202views Multimedia» more  MMM 2005»
14 years 1 months ago
Image Mining and Retrieval Using Hierarchical Support Vector Machines
For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been la...
Ross Brown, Binh Pham
ESWA
2007
127views more  ESWA 2007»
13 years 7 months ago
Clustering support vector machines for protein local structure prediction
Understanding the sequence-to-structure relationship is a central task in bioinformatics research. Adequate knowledge about this relationship can potentially improve accuracy for ...
Wei Zhong, Jieyue He, Robert W. Harrison, Phang C....
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...
COLING
2010
13 years 2 months ago
Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...
Son Doan, Hua Xu
TITB
2008
102views more  TITB 2008»
13 years 7 months ago
Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
Baek Hwan Cho, Hwanjo Yu, Jong Shill Lee, Young Jo...