Using Dimension Reduction to Improve the Classification of High-dimensional Data.
Andreas GrünauerMarkus VinczePublished in: CoRR (2015)
Keyphrases
- dimension reduction
- high dimensional data
- high dimensionality
- low dimensional
- high dimensional
- dimensionality reduction
- linear discriminant analysis
- nearest neighbor
- feature extraction
- subspace clustering
- similarity search
- high dimensions
- variable selection
- manifold learning
- random projections
- principal component analysis
- data points
- feature space
- small sample size
- data sets
- data analysis
- lower dimensional
- input space
- sparse representation
- singular value decomposition
- dimensional data
- high dimensional spaces
- original data
- high dimensional data analysis
- feature selection
- unsupervised learning
- dimensionality reduction methods
- nonlinear dimensionality reduction
- neural network
- support vector machine svm
- input data
- support vector machine
- active learning
- subspace learning
- similarity measure
- image processing
- real world