Kernel Feature Selection via Conditional Covariance Minimization.
Jianbo ChenMitchell SternMartin J. WainwrightMichael I. JordanPublished in: NIPS (2017)
Keyphrases
- feature selection
- support vector
- class separability
- feature space
- kernel learning
- kernel function
- text categorization
- mutual information
- kernel methods
- hilbert schmidt
- multiple kernel learning
- selected features
- text classification
- objective function
- feature extraction
- feature selection algorithms
- machine learning
- classification accuracy
- kernel machines
- feature subset
- feature set
- supervised learning tasks
- model selection
- covariance matrix
- reproducing kernel hilbert space
- kernel matrix
- dimensionality reduction
- linear svm
- ensemble learning
- microarray data
- knn
- support vector machine
- multi class
- pairwise
- multi task
- discriminant analysis
- linear discriminant analysis
- random field model
- method for feature selection
- multivariate gaussian distribution
- data sets