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Table 8 Some main differences and similarities of the PCA, NMF and SC methods

From: High level feature extraction for the self-taught learning algorithm

Number of bases Less or same Less, same or more Less, same or more
wrt input dimension    
Bases orthogonality Yes No No
Bases learning Analytic Iterative Iterative
Data representation Linear Non-linear Non-linear
Data sign Any Positive Any
Sparsity No Uncontrollable Adjustable