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3DPVT
2006
IEEE
197views Visualization» more  3DPVT 2006»
13 years 10 months ago
Aerial LiDAR Data Classification Using Support Vector Machines (SVM)
We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
PR
2006
229views more  PR 2006»
13 years 6 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
AAAI
2008
13 years 8 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
INFORMS
2010
177views more  INFORMS 2010»
13 years 4 months ago
Binarized Support Vector Machines
The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have bec...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
BMCBI
2011
12 years 10 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...