mixclass

Get the classification from a mixture model.

Input Arguments:

• DATA is a matrix of observations (n by p).
• WGTS (mixing coefficients), MUS (means), VARS (covariances) correspond to the finite mixture model. These are usually obtained from mbcfinmix or mbclust.
  

Output Arguments:

• ERR is a vector of the classification uncertainty.
• CLABS is the cluster labels.

Synopsis

[CLABS,ERR] = MIXCLASS(DATA,WGTS,MUS,VARS)

References:

Model-Based Clustering Toolbox documentation.

Model-Based Clustering homepage.