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KAIS
2010
144views more  KAIS 2010»
13 years 7 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
IJON
2006
119views more  IJON 2006»
13 years 9 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa
IFIP7
2001
Springer
137views Optimization» more  IFIP7 2001»
14 years 1 months ago
Data Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various fields. Much more recently, SVMs have become the tool of choice for problems...
Olvi L. Mangasarian
ISBI
2008
IEEE
14 years 9 months ago
Support vector machine for data on manifolds: An application to image analysis
The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
3DPVT
2006
IEEE
197views Visualization» more  3DPVT 2006»
14 years 23 days 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...