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| author | Daniel Wolff |
|---|---|
| date | Fri, 19 Aug 2016 13:07:06 +0200 |
| parents | |
| children |
| rev | line source |
|---|---|
| Daniel@0 | 1 <html> |
| Daniel@0 | 2 <head> |
| Daniel@0 | 3 <title> |
| Daniel@0 | 4 Netlab Reference Manual rbfsetbf |
| Daniel@0 | 5 </title> |
| Daniel@0 | 6 </head> |
| Daniel@0 | 7 <body> |
| Daniel@0 | 8 <H1> rbfsetbf |
| Daniel@0 | 9 </H1> |
| Daniel@0 | 10 <h2> |
| Daniel@0 | 11 Purpose |
| Daniel@0 | 12 </h2> |
| Daniel@0 | 13 Set basis functions of RBF from data. |
| Daniel@0 | 14 |
| Daniel@0 | 15 <p><h2> |
| Daniel@0 | 16 Synopsis |
| Daniel@0 | 17 </h2> |
| Daniel@0 | 18 <PRE> |
| Daniel@0 | 19 net = rbfsetbf(net, options, x) |
| Daniel@0 | 20 </PRE> |
| Daniel@0 | 21 |
| Daniel@0 | 22 |
| Daniel@0 | 23 <p><h2> |
| Daniel@0 | 24 Description |
| Daniel@0 | 25 </h2> |
| Daniel@0 | 26 <CODE>net = rbfsetbf(net, options, x)</CODE> sets the basis functions of the |
| Daniel@0 | 27 RBF network <CODE>net</CODE> so that they model the unconditional density of the |
| Daniel@0 | 28 dataset <CODE>x</CODE>. This is done by training a GMM with spherical covariances |
| Daniel@0 | 29 using <CODE>gmmem</CODE>. The <CODE>options</CODE> vector is passed to <CODE>gmmem</CODE>. |
| Daniel@0 | 30 The widths of the functions are set by a call to <CODE>rbfsetfw</CODE>. |
| Daniel@0 | 31 |
| Daniel@0 | 32 <p><h2> |
| Daniel@0 | 33 See Also |
| Daniel@0 | 34 </h2> |
| Daniel@0 | 35 <CODE><a href="rbftrain.htm">rbftrain</a></CODE>, <CODE><a href="rbfsetfw.htm">rbfsetfw</a></CODE>, <CODE><a href="gmmem.htm">gmmem</a></CODE><hr> |
| Daniel@0 | 36 <b>Pages:</b> |
| Daniel@0 | 37 <a href="index.htm">Index</a> |
| Daniel@0 | 38 <hr> |
| Daniel@0 | 39 <p>Copyright (c) Ian T Nabney (1996-9) |
| Daniel@0 | 40 |
| Daniel@0 | 41 |
| Daniel@0 | 42 </body> |
| Daniel@0 | 43 </html> |