Hilbert–Schmidt component analysis

Abstract

We propose a feature extraction algorithm, based on the Hilbert–Schmidt independence criterion (HSIC) and the maximum dependence – minimum redundancy approach. Experiments with classification data sets demonstrate that suggested Hilbert–Schmidt component analysis (HSCA) algorithm in certain cases may be more efficient than other considered approaches.

Keywords

• feature extraction
• dimensionality reduction
• HSCA
• Hilbert–Schmidt independence criterion
• kernel methods