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| author | wolffd |
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| date | Tue, 10 Feb 2015 15:05:51 +0000 |
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| 1 <html> | |
| 2 <head> | |
| 3 <title> | |
| 4 Netlab Reference Manual mdnpost | |
| 5 </title> | |
| 6 </head> | |
| 7 <body> | |
| 8 <H1> mdnpost | |
| 9 </H1> | |
| 10 <h2> | |
| 11 Purpose | |
| 12 </h2> | |
| 13 Computes the posterior probability for each MDN mixture component. | |
| 14 | |
| 15 <p><h2> | |
| 16 Synopsis | |
| 17 </h2> | |
| 18 <PRE> | |
| 19 post = mdnpost(mixparams, t) | |
| 20 [post, a] = mdnpost(mixparams, t) | |
| 21 </PRE> | |
| 22 | |
| 23 | |
| 24 <p><h2> | |
| 25 Description | |
| 26 </h2> | |
| 27 <CODE>post = mdnpost(mixparams, t)</CODE> computes the posterior | |
| 28 probability <CODE>p(j|t)</CODE> of each | |
| 29 data vector in <CODE>t</CODE> under the Gaussian mixture model represented by the | |
| 30 corresponding entries in <CODE>mixparams</CODE>. Each row of <CODE>t</CODE> represents a | |
| 31 single vector. | |
| 32 | |
| 33 <p><CODE>[post, a] = mdnpost(mixparams, t)</CODE> also computes the activations | |
| 34 <CODE>a</CODE> (i.e. the probability <CODE>p(t|j)</CODE> of the data conditioned on | |
| 35 each component density) for a Gaussian mixture model. | |
| 36 | |
| 37 <p><h2> | |
| 38 See Also | |
| 39 </h2> | |
| 40 <CODE><a href="mdngrad.htm">mdngrad</a></CODE>, <CODE><a href="mdnprob.htm">mdnprob</a></CODE><hr> | |
| 41 <b>Pages:</b> | |
| 42 <a href="index.htm">Index</a> | |
| 43 <hr> | |
| 44 <p>Copyright (c) Ian T Nabney (1996-9) | |
| 45 <p>David J Evans (1998) | |
| 46 | |
| 47 </body> | |
| 48 </html> |