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comparison toolboxes/FullBNT-1.0.7/nethelp3.3/confmat.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 confmat | |
| 5 </title> | |
| 6 </head> | |
| 7 <body> | |
| 8 <H1> confmat | |
| 9 </H1> | |
| 10 <h2> | |
| 11 Purpose | |
| 12 </h2> | |
| 13 Compute a confusion matrix. | |
| 14 | |
| 15 <p><h2> | |
| 16 Synopsis | |
| 17 </h2> | |
| 18 <PRE> | |
| 19 [C, rate] = confmat(y, t)</PRE> | |
| 20 | |
| 21 | |
| 22 <p><h2> | |
| 23 Description | |
| 24 </h2> | |
| 25 <CODE>[C, rate] = confmat(y, t)</CODE> computes the confusion matrix <CODE>C</CODE> | |
| 26 and classification performance <CODE>rate</CODE> for the predictions mat{y} | |
| 27 compared with the targets <CODE>t</CODE>. The data is assumed to be in a | |
| 28 1-of-N encoding, unless there is just one column, when it is assumed to | |
| 29 be a 2 class problem with a 0-1 encoding. Each row of <CODE>y</CODE> and <CODE>t</CODE> | |
| 30 corresponds to a single example. | |
| 31 | |
| 32 <p>In the confusion matrix, the rows represent the true classes and the | |
| 33 columns the predicted classes. The vector <CODE>rate</CODE> has two entries: | |
| 34 the percentage of correct classifications and the total number of | |
| 35 correct classifications. | |
| 36 | |
| 37 <p><h2> | |
| 38 See Also | |
| 39 </h2> | |
| 40 <CODE><a href="conffig.htm">conffig</a></CODE>, <CODE><a href="demtrain.htm">demtrain</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 | |
| 46 | |
| 47 </body> | |
| 48 </html> |