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1 <html>
2 <head>
3 <title>
4 Netlab Reference Manual gmmem
5 </title>
6 </head>
7 <body>
8 <H1> gmmem
9 </H1>
10 <h2>
11 Purpose
12 </h2>
13 EM algorithm for Gaussian mixture model.
14
15 <p><h2>
16 Synopsis
17 </h2>
18 <PRE>
19
20 [mix, options, errlog] = gmmem(mix, x, options)
21 </PRE>
22
23
24 <p><h2>
25 Description
26 </h2>
27 <CODE>[mix, options, errlog] = gmmem(mix, x, options)</CODE> uses the Expectation
28 Maximization algorithm of Dempster et al. to estimate the parameters of
29 a Gaussian mixture model defined by a data structure <CODE>mix</CODE>.
30 The matrix <CODE>x</CODE> represents the data whose expectation
31 is maximized, with each row corresponding to a vector.
32
33 The optional parameters have the following interpretations.
34
35 <p><CODE>options(1)</CODE> is set to 1 to display error values; also logs error
36 values in the return argument <CODE>errlog</CODE>.
37 If <CODE>options(1)</CODE> is set to 0,
38 then only warning messages are displayed. If <CODE>options(1)</CODE> is -1,
39 then nothing is displayed.
40
41 <p><CODE>options(3)</CODE> is a measure of the absolute precision required of the error
42 function at the solution. If the change in log likelihood between two steps of
43 the EM algorithm is less than this value, then the function terminates.
44
45 <p><CODE>options(5)</CODE> is set to 1 if a covariance matrix is reset to its
46 original value when any of its singular values are too small (less
47 than MIN_COVAR which has the value eps).
48 With the default value of 0 no action is taken.
49
50 <p><CODE>options(14)</CODE> is the maximum number of iterations; default 100.
51
52 <p>The optional return value <CODE>options</CODE> contains the final error value
53 (i.e. data log likelihood) in
54 <CODE>options(8)</CODE>.
55
56 <p><h2>
57 Examples
58 </h2>
59 The following code fragment sets up a Gaussian mixture model, initialises
60 the parameters from the data, sets the options and trains the model.
61 <PRE>
62
63 mix = gmm(inputdim, ncentres, 'full');
64
65 <p>options = foptions;
66 options(14) = 5;
67 mix = gmminit(mix, data, options);
68
69 <p>options(1) = 1; % Prints out error values.
70 options(14) = 30; % Max. number of iterations.
71
72 <p>mix = gmmem(mix, data, options);
73 </PRE>
74
75
76 <p><h2>
77 See Also
78 </h2>
79 <CODE><a href="gmm.htm">gmm</a></CODE>, <CODE><a href="gmminit.htm">gmminit</a></CODE><hr>
80 <b>Pages:</b>
81 <a href="index.htm">Index</a>
82 <hr>
83 <p>Copyright (c) Ian T Nabney (1996-9)
84
85
86 </body>
87 </html>