EM experiment #2: red class, full covariances

Number of Gaussians, assumes full covariance matrices

Choose number of Gaussians in mixture model

Assumes full covariance matrices

Compute EM algorithm

RowBox[{Timing, [, RowBox[{RowBox[{em, , =, , RowBox[{EM, [, RowBox[{data1, ,, initFull, ,, 0.001}], ]}]}], ;}], ]}]

RowBox[{{, RowBox[{RowBox[{0.11, , Second}], ,, Null}], }}]

Visualization

Initial model

AnnularAllPlot[c1, rr1, rr2, em//First] ;

[Graphics:../HTMLFiles/index_36.gif]

Final model

AnnularAllPlot[c1, rr1, rr2, em//Last] ;

[Graphics:../HTMLFiles/index_38.gif]

Plot log-likelihood of data given the model as a function of EM iteration

PlotLogLikelihood[em, data1] ;

[Graphics:../HTMLFiles/index_40.gif]

Save solution

Created by Mathematica  (September 8, 2003)