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comparison toolboxes/FullBNT-1.0.7/nethelp3.3/demkmn1.htm @ 0:e9a9cd732c1e tip
first hg version after svn
| 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 demkmean | |
| 5 </title> | |
| 6 </head> | |
| 7 <body> | |
| 8 <H1> demkmean | |
| 9 </H1> | |
| 10 <h2> | |
| 11 Purpose | |
| 12 </h2> | |
| 13 Demonstrate simple clustering model trained with K-means. | |
| 14 | |
| 15 <p><h2> | |
| 16 Synopsis | |
| 17 </h2> | |
| 18 <PRE> | |
| 19 demkmean</PRE> | |
| 20 | |
| 21 | |
| 22 <p><h2> | |
| 23 Description | |
| 24 </h2> | |
| 25 The problem consists of data in a two-dimensional space. | |
| 26 The data is | |
| 27 drawn from three spherical Gaussian distributions with priors 0.3, | |
| 28 0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and standard deviations | |
| 29 0.2, 0.5 and 1.0. The first figure contains a | |
| 30 scatter plot of the data. The data is the same as in <CODE>demgmm1</CODE>. | |
| 31 | |
| 32 <p>A cluster model with three components is trained using the batch | |
| 33 K-means algorithm. The matrix of centres is printed after training. | |
| 34 The second | |
| 35 figure shows the data labelled with a colour derived from the corresponding | |
| 36 cluster | |
| 37 | |
| 38 <p><h2> | |
| 39 See Also | |
| 40 </h2> | |
| 41 <CODE><a href="dem2ddat.htm">dem2ddat</a></CODE>, <CODE><a href="demgmm1.htm">demgmm1</a></CODE>, <CODE><a href="knn1.htm">knn1</a></CODE>, <CODE><a href="kmeans.htm">kmeans</a></CODE><hr> | |
| 42 <b>Pages:</b> | |
| 43 <a href="index.htm">Index</a> | |
| 44 <hr> | |
| 45 <p>Copyright (c) Ian T Nabney (1996-9) | |
| 46 | |
| 47 | |
| 48 </body> | |
| 49 </html> |