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author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 <html>
Daniel@0 2 <head>
Daniel@0 3 <title>
Daniel@0 4 Netlab Reference Manual confmat
Daniel@0 5 </title>
Daniel@0 6 </head>
Daniel@0 7 <body>
Daniel@0 8 <H1> confmat
Daniel@0 9 </H1>
Daniel@0 10 <h2>
Daniel@0 11 Purpose
Daniel@0 12 </h2>
Daniel@0 13 Compute a confusion matrix.
Daniel@0 14
Daniel@0 15 <p><h2>
Daniel@0 16 Synopsis
Daniel@0 17 </h2>
Daniel@0 18 <PRE>
Daniel@0 19 [C, rate] = confmat(y, t)</PRE>
Daniel@0 20
Daniel@0 21
Daniel@0 22 <p><h2>
Daniel@0 23 Description
Daniel@0 24 </h2>
Daniel@0 25 <CODE>[C, rate] = confmat(y, t)</CODE> computes the confusion matrix <CODE>C</CODE>
Daniel@0 26 and classification performance <CODE>rate</CODE> for the predictions mat{y}
Daniel@0 27 compared with the targets <CODE>t</CODE>. The data is assumed to be in a
Daniel@0 28 1-of-N encoding, unless there is just one column, when it is assumed to
Daniel@0 29 be a 2 class problem with a 0-1 encoding. Each row of <CODE>y</CODE> and <CODE>t</CODE>
Daniel@0 30 corresponds to a single example.
Daniel@0 31
Daniel@0 32 <p>In the confusion matrix, the rows represent the true classes and the
Daniel@0 33 columns the predicted classes. The vector <CODE>rate</CODE> has two entries:
Daniel@0 34 the percentage of correct classifications and the total number of
Daniel@0 35 correct classifications.
Daniel@0 36
Daniel@0 37 <p><h2>
Daniel@0 38 See Also
Daniel@0 39 </h2>
Daniel@0 40 <CODE><a href="conffig.htm">conffig</a></CODE>, <CODE><a href="demtrain.htm">demtrain</a></CODE><hr>
Daniel@0 41 <b>Pages:</b>
Daniel@0 42 <a href="index.htm">Index</a>
Daniel@0 43 <hr>
Daniel@0 44 <p>Copyright (c) Ian T Nabney (1996-9)
Daniel@0 45
Daniel@0 46
Daniel@0 47 </body>
Daniel@0 48 </html>