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1 <html>
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2 <head>
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3 <title>
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4 Netlab Reference Manual gtmem
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5 </title>
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6 </head>
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7 <body>
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8 <H1> gtmem
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9 </H1>
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10 <h2>
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11 Purpose
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12 </h2>
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13 EM algorithm for Generative Topographic Mapping.
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14
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15 <p><h2>
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16 Synopsis
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17 </h2>
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18 <PRE>
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19
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20 [net, options, errlog] = gtmem(net, t, options)
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21 </PRE>
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22
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23
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24 <p><h2>
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25 Description
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26 </h2>
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27 <CODE>[net, options, errlog] = gtmem(net, t, options)</CODE> uses the Expectation
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28 Maximization algorithm to estimate the parameters of
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29 a GTM defined by a data structure <CODE>net</CODE>.
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30 The matrix <CODE>t</CODE> represents the data whose expectation
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31 is maximized, with each row corresponding to a vector. It is assumed
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32 that the latent data <CODE>net.X</CODE> has been set following a call to
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33 <CODE>gtminit</CODE>, for example.
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34
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35 The optional parameters have the following interpretations.
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36
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37 <p><CODE>options(1)</CODE> is set to 1 to display error values; also logs error
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38 values in the return argument <CODE>errlog</CODE>.
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39 If <CODE>options(1)</CODE> is set to 0,
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40 then only warning messages are displayed. If <CODE>options(1)</CODE> is -1,
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41 then nothing is displayed.
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42
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43 <p><CODE>options(3)</CODE> is a measure of the absolute precision required of the error
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44 function at the solution. If the change in log likelihood between two steps of
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45 the EM algorithm is less than this value, then the function terminates.
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46
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47 <p><CODE>options(14)</CODE> is the maximum number of iterations; default 100.
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48
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49 <p>The optional return value <CODE>options</CODE> contains the final error value
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50 (i.e. data log likelihood) in
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51 <CODE>options(8)</CODE>.
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52
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53 <p><h2>
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54 Examples
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55 </h2>
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56 The following code fragment sets up a GTM, initialises
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57 the latent data sample and RBF
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58 parameters from the data, sets the options and trains the model.
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59 <PRE>
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60
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61 % Create and initialise GTM model
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62 net = gtm(latentdim, nlatent, datadim, numrbfcentres, ...
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63 'gaussian', 0.1);
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64
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65 <p>options = foptions;
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66 options(1) = -1;
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67 options(7) = 1; % Set width factor of RBF
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68 net = gtminit(net, options, data, 'regular', latentshape, [4 4]);
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69
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70 <p>options = foptions;
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71 options(14) = 30;
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72 options(1) = 1;
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73 [net, options] = gtmem(net, data, options);
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74 </PRE>
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75
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76
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77 <p><h2>
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78 See Also
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79 </h2>
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80 <CODE><a href="gtm.htm">gtm</a></CODE>, <CODE><a href="gtminit.htm">gtminit</a></CODE><hr>
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81 <b>Pages:</b>
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82 <a href="index.htm">Index</a>
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83 <hr>
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84 <p>Copyright (c) Ian T Nabney (1996-9)
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85
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86
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87 </body>
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88 </html> |
