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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual demgmm1
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> demgmm1
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Demonstrate density modelling with a Gaussian mixture model.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 demgmm1</PRE>
wolffd@0 20
wolffd@0 21
wolffd@0 22 <p><h2>
wolffd@0 23 Description
wolffd@0 24 </h2>
wolffd@0 25 The problem consists of modelling data generated by a mixture of three
wolffd@0 26 Gaussians in 2 dimensions. The priors are 0.3,
wolffd@0 27 0.5 and 0.2; the centres are (2, 3.5), (0, 0) and (0,2); the variances
wolffd@0 28 are 0.2, 0.5 and 1.0. The first figure contains a
wolffd@0 29 scatter plot of the data.
wolffd@0 30
wolffd@0 31 <p>A Gaussian mixture model with three components is trained using EM. The
wolffd@0 32 parameter vector is printed before training and after training. The user
wolffd@0 33 should press any key to continue at these points. The parameter vector
wolffd@0 34 consists of priors (the column), centres (given as (x, y) pairs as
wolffd@0 35 the next two columns), and variances (the last column).
wolffd@0 36
wolffd@0 37 <p>The second figure is a 3 dimensional view of the density function, while
wolffd@0 38 the third shows the 1-standard deviation circles for the three components of
wolffd@0 39 the mixture model.
wolffd@0 40
wolffd@0 41 <p><h2>
wolffd@0 42 See Also
wolffd@0 43 </h2>
wolffd@0 44 <CODE><a href="gmm.htm">gmm</a></CODE>, <CODE><a href="gmminit.htm">gmminit</a></CODE>, <CODE><a href="gmmem.htm">gmmem</a></CODE>, <CODE><a href="gmmprob.htm">gmmprob</a></CODE>, <CODE><a href="gmmunpak.htm">gmmunpak</a></CODE><hr>
wolffd@0 45 <b>Pages:</b>
wolffd@0 46 <a href="index.htm">Index</a>
wolffd@0 47 <hr>
wolffd@0 48 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 49
wolffd@0 50
wolffd@0 51 </body>
wolffd@0 52 </html>