Trace Ratio Criterion Based Large Margin Subspace Learning for Feature Selection.
Hui LuoJiqing HanPublished in: IEEE Access (2019)
Keyphrases
- subspace learning
- selecting relevant features
- feature selection
- dimensionality reduction
- learning algorithm
- support vector
- manifold learning
- data representation
- principal component analysis
- low dimensional
- maximum margin criterion
- high dimensional data
- sparse representation
- semi supervised
- feature extraction
- face recognition
- mutual information
- text classification
- high dimensionality
- dimension reduction
- sparse coding
- data sets
- unsupervised learning
- support vector machine
- high dimensional
- feature space
- subspace learning algorithm
- small number
- feature vectors
- multiscale
- machine learning