Subspace techniques for large-scale feature selection.
Larry P. HeckJames H. McClellanPublished in: ICASSP (4) (1993)
Keyphrases
- feature selection
- feature space
- dimensionality reduction
- feature extraction
- text categorization
- high dimensionality
- low dimensional
- support vector
- small scale
- high dimensional data
- machine learning
- method for feature selection
- subspace learning
- classification models
- text classification
- subspace clustering
- irrelevant features
- unsupervised learning
- multi task
- real life
- classification accuracy
- feature subset
- feature selection algorithms
- principal component analysis
- high dimensional
- discriminative features
- small sample
- mutual information
- feature subspace
- unsupervised feature selection
- real world
- clustering high dimensional data