Asymptotics and practical aspects of testing normality with kernel methods.
Natsumi MakigusaKanta NaitoPublished in: J. Multivar. Anal. (2020)
Keyphrases
- kernel methods
- kernel function
- feature space
- learning problems
- support vector
- kernel matrices
- support vector machine
- reproducing kernel hilbert space
- kernel matrix
- sufficient conditions
- machine learning
- kernel pca
- kernel fisher discriminant analysis
- kernel parameters
- high dimensional feature space
- graph kernels
- learning tasks
- similarity function
- kernel learning
- real world
- classification accuracy
- feature selection
- kernel principal component analysis
- kernel trick
- data mining
- data sets