Title of article :
Determining the number of principal components for best reconstruction
Author/Authors :
S. Joe Qin and Ricardo Dunia، نويسنده ,
Abstract :
A well-de®ned variance of reconstruction error (VRE) is proposed to determine the number of principal components in a PCA
model for best reconstruction. Unlike most other methods in the literature, this proposed VRE method has a guaranteed minimum
over the number of PCʹs corresponding to the best reconstruction. Therefore, it avoids the arbitrariness of other methods with
monotonic indices. The VRE can also be used to remove variables that are little correlated with others and cannot be reliably
reconstructed from the correlation-based PCA model. The eectiveness of this method is demonstrated with a simulated process.
Keywords :
Principal component analysis , Missing values , Sensor reconstruction , principal component subspace , Residual subspace
Journal title :
Astroparticle Physics