Hilbert–Schmidt component analysis - Daniušis, Povilas; Vaitkus, Pranas; Petkevičius, Linas (Lietuvos matematikos rinkinys, 2016)
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