Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data
Mathieu FauvelAlberto VillaJocelyn ChanussotJón Atli BenediktssonPublished in: CoRR (2012)
Keyphrases
- high dimensional data
- high dimensionality
- dimension reduction
- high dimensional
- dimensionality reduction
- input space
- feature space
- low dimensional
- subspace clustering
- support vector
- regression problems
- small sample size
- nearest neighbor
- data sets
- pattern recognition
- high dimensional datasets
- high dimensions
- data points
- manifold learning
- data analysis
- clustering high dimensional data
- dimensional data
- similarity search
- high dimensional feature spaces
- sparse representation
- machine learning
- kernel function
- feature selection
- feature extraction
- feature vectors
- high dimensional data sets
- linear discriminant analysis
- distance function
- image classification
- support vector machine
- decision trees
- class labels
- support vector machine svm
- training set
- kernel machines
- dimensionality reduction methods
- variable weighting
- high dimensional spaces
- low rank
- model selection
- text classification
- input data
- image data
- data mining
- neural network