| CDpcaSummary {biplotbootGUI} | R Documentation |
Clustering and Disjoint Principal Component Analysis Summary
Description
Produce a list of summary measures to evaluate the result of the CDPCA
Usage
CDpcaSummary(obj)
Arguments
obj |
An object of the type produced by CDpca |
Value
CDpcaSummary returns the following values associated to the loop where the best result was produced:
Number of the loops
Number of iterations
Value of the objective function F
Frobenius norm of the error matrix
Between cluster deviance (percentage)
Explained variance by CDpca components (percentage)
Pseudo Confusion Matrix (if available)
Author(s)
Eloisa Macedo macedo@ua.pt, Adelaide Freitas adelaide@ua.pt, Maurizio Vichi maurizio.vichi@uniroma1.it
References
Vichi, M and Saporta, G. (2009). Clustering and disjoint principal component analysis. Computational Statistics and Data Analysis, 53, 3194-3208.
Macedo, E. and Freitas, A. (2015). The alternating least-squares algorithm for CDPCA. Communications in Computer and Information Science (CCIS), Springer Verlag pp. 173-191.