Wavelet-based Bayesian approximate kernel method for high-dimensional data analysis.
Wenxing GuoXueying ZhangBei JiangLinglong KongYaozhong HuPublished in: Comput. Stat. (2024)
Keyphrases
- kernel methods
- high dimensional data analysis
- dimension reduction
- kernel function
- preprocessing step
- support vector
- feature space
- reproducing kernel hilbert space
- learning problems
- high dimensional
- support vector machine
- multimodal data
- kernel matrix
- learning tasks
- machine learning
- maximum likelihood
- high dimensional feature space
- least squares
- dimensionality reduction
- dimensionality reduction methods
- classification accuracy
- multiple kernel learning
- supervised dimensionality reduction
- kernel pca
- neural network
- variable selection
- data mining
- preprocessing
- face recognition
- computer vision