schp

PURPOSE

Class implementing a linear projection subspace of arbitrary dimensions estimated through SCPP

This is a script file.

Class implementing a linear projection subspace of arbitrary dimensions estimated through SCPP

This function calls:

fixLabels Enforces cluster labels to be in the range 1:K
palette Determines colours used for visualisation
pcacomp Returns the principal components of (X) specified in vector (index)
success_ratio Quantifies accuracy with which a binary partition splits data containing two or more clusters
f_sc Second smallest eigenvalue of Normalised Laplacian and difference to 3rd smallest
schp Class implementing a linear projection subspace of arbitrary dimensions estimated through SCPP
scpp Spectral Clustering Projection Pursuit (SCPP) (divisive clustering is implemented in scppdc.m)
scppNJW Clustering of projected data using Ng, Jordan and Weiss (2002) normalised spectral clustering algorithm
scpp_def_sigma Default scaling parameter (sigma) for Gaussian kernel used to estimate kernel/ similarity matrix in SCPP

This function is called by:

schp Class implementing a linear projection subspace of arbitrary dimensions estimated through SCPP
scpp Spectral Clustering Projection Pursuit (SCPP) (divisive clustering is implemented in scppdc.m)