A gradient-based variable selection for binary classification in reproducing kernel Hilbert space.
Jongkyeong KangSeung Jun ShinPublished in: CoRR (2021)
Keyphrases
- binary classification
- variable selection
- reproducing kernel hilbert space
- learning problems
- support vector
- kernel methods
- cross validation
- kernel function
- loss function
- high dimensional
- generalization error
- multi class
- input variables
- learning tasks
- support vector machine
- model selection
- machine learning algorithms
- dimension reduction
- machine learning
- learning algorithm
- semi supervised learning
- feature selection
- kernel matrix
- supervised learning
- cost sensitive
- euclidean space
- gaussian process
- ls svm
- high dimensional data
- multi label
- multi task learning
- multi task
- hyperparameters
- input space
- reinforcement learning
- ensemble methods
- training set
- data sets