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first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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wolffd@0 | 1 <html> |
wolffd@0 | 2 <head> |
wolffd@0 | 3 <title> |
wolffd@0 | 4 Netlab Reference Manual demknn1 |
wolffd@0 | 5 </title> |
wolffd@0 | 6 </head> |
wolffd@0 | 7 <body> |
wolffd@0 | 8 <H1> demknn1 |
wolffd@0 | 9 </H1> |
wolffd@0 | 10 <h2> |
wolffd@0 | 11 Purpose |
wolffd@0 | 12 </h2> |
wolffd@0 | 13 Demonstrate nearest neighbour classifier. |
wolffd@0 | 14 |
wolffd@0 | 15 <p><h2> |
wolffd@0 | 16 Synopsis |
wolffd@0 | 17 </h2> |
wolffd@0 | 18 <PRE> |
wolffd@0 | 19 demknn1</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 data in a two-dimensional space. |
wolffd@0 | 26 The data is |
wolffd@0 | 27 drawn from three spherical Gaussian distributions with priors 0.3, |
wolffd@0 | 28 0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and standard deviations |
wolffd@0 | 29 0.2, 0.5 and 1.0. The first figure contains a |
wolffd@0 | 30 scatter plot of the data. The data is the same as in <CODE>demgmm1</CODE>. |
wolffd@0 | 31 |
wolffd@0 | 32 <p>The second |
wolffd@0 | 33 figure shows the data labelled with the corresponding class given |
wolffd@0 | 34 by the classifier. |
wolffd@0 | 35 |
wolffd@0 | 36 <p><h2> |
wolffd@0 | 37 See Also |
wolffd@0 | 38 </h2> |
wolffd@0 | 39 <CODE><a href="dem2ddat.htm">dem2ddat</a></CODE>, <CODE><a href="demgmm1.htm">demgmm1</a></CODE>, <CODE><a href="knn.htm">knn</a></CODE><hr> |
wolffd@0 | 40 <b>Pages:</b> |
wolffd@0 | 41 <a href="index.htm">Index</a> |
wolffd@0 | 42 <hr> |
wolffd@0 | 43 <p>Copyright (c) Ian T Nabney (1996-9) |
wolffd@0 | 44 |
wolffd@0 | 45 |
wolffd@0 | 46 </body> |
wolffd@0 | 47 </html> |