Dimension reduction using evolutionary Support Vector Machines.
Ji Hua AngEu Jin TeohC. H. TanK. C. GohKay Chen TanPublished in: IEEE Congress on Evolutionary Computation (2008)
Keyphrases
- dimension reduction
- support vector
- linear discriminant analysis
- learning machines
- large margin classifiers
- feature selection
- feature extraction
- principal component analysis
- high dimensional problems
- data mining and machine learning
- random projections
- discriminative information
- high dimensional
- support vector machine
- low dimensional
- variable selection
- discriminant analysis
- high dimensional data analysis
- cluster analysis
- manifold learning
- singular value decomposition
- dimensionality reduction
- high dimensionality
- loss function
- high dimensional data
- partial least squares
- svm classifier
- kernel methods
- maximum margin
- feature space
- kernel function
- multiple kernel learning
- data sets
- dimension reduction methods
- pattern recognition
- model selection
- unsupervised learning
- training samples
- database