Description: Core-based principal component analysis is a nonlinear feature extraction method, which maps data the input space to the feature space through a nonlinear mapping, and then carries out the usual principal component analysis in the feature space. The inner product calculation uses a Nuclear function instead
To Search:
File list (Check if you may need any files):
kPCA-master
...........\.gitattributes
...........\.gitignore
...........\kpca.py
...........\main.py
Download