Efficient Classification for Large-scale Problems by Multiple LDA Subspaces.
Martina UrayPeter M. RothHorst BischofPublished in: VISAPP (1) (2009)
Keyphrases
- small sample size
- high dimensionality
- feature space
- classification accuracy
- machine learning
- feature extraction
- dimension reduction
- high dimensional
- sample size
- high dimensional data
- support vector machine svm
- real world
- subspace analysis
- pattern recognition problems
- latent dirichlet allocation
- linear discriminant analysis
- optimization problems
- support vector machine
- face recognition
- decision trees
- data mining
- image classification
- generative model
- dimensionality reduction
- nearest neighbor
- benchmark datasets
- pattern recognition
- support vector
- training data
- lower dimensional
- neural network