DD_tools: pca_dd

PCA_DD Principal Component data description

       W = PCA_DD(A,FRACREJ,N)
       W = PCA_DD(A,FRACREJ,VAR)

 Fit a Principal Component Analysis data description by estimating
 first a PCA on the target class, and mapping the training data onto
 the PCA subspace. The distance between the original objects and the
 mapped objects is used to detect outliers. 
 The number of dimensions of the PCA can be supplied by N.
 Alternatively the fraction of explained variance can be given (in
 VAR).

 Default: FRACRE=0.05, VAR=0.9



Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
Faculty EWI, Delft University of Technology
P.O. Box 5031, 2600 GA Delft, The Netherlands