Data preprocessing & normalization

Unit variance preprocessing

In the same way as for standard linear PCA, normalizing the data to unit variance can be helpful in some cases. In nonlinear PCA, data can be normalized by using the option pre_unit_variance .

[pc,net,network]=nlpca(data,3,'pre_unit_variance','yes');

Linear PCA preprocessing

To avoid bad random initializations, NLPCA can be started with the linear PCA solution, and hence only needs to optimize the transformation from a perfect linear solution into a good curved nonlinear solution. This PCA pre-processing can be done by adding the option: 'pre_pca','yes'

For example:

[pc,net,network]=nlpca(data,3,'pre_pca','yes')

see also

→ Robustness & reproducibility