annotate toolboxes/FullBNT-1.0.7/netlab3.3/conffig.m @ 0:cc4b1211e677 tip

initial commit to HG from Changeset: 646 (e263d8a21543) added further path and more save "camirversion.m"
author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 function fh=conffig(y, t)
Daniel@0 2 %CONFFIG Display a confusion matrix.
Daniel@0 3 %
Daniel@0 4 % Description
Daniel@0 5 % CONFFIG(Y, T) displays the confusion matrix and classification
Daniel@0 6 % performance for the predictions mat{y} compared with the targets T.
Daniel@0 7 % The data is assumed to be in a 1-of-N encoding, unless there is just
Daniel@0 8 % one column, when it is assumed to be a 2 class problem with a 0-1
Daniel@0 9 % encoding. Each row of Y and T corresponds to a single example.
Daniel@0 10 %
Daniel@0 11 % In the confusion matrix, the rows represent the true classes and the
Daniel@0 12 % columns the predicted classes.
Daniel@0 13 %
Daniel@0 14 % FH = CONFFIG(Y, T) also returns the figure handle FH which can be
Daniel@0 15 % used, for instance, to delete the figure when it is no longer needed.
Daniel@0 16 %
Daniel@0 17 % See also
Daniel@0 18 % CONFMAT, DEMTRAIN
Daniel@0 19 %
Daniel@0 20
Daniel@0 21 % Copyright (c) Ian T Nabney (1996-2001)
Daniel@0 22
Daniel@0 23 [C, rate] = confmat(y, t);
Daniel@0 24
Daniel@0 25 fh = figure('Name', 'Confusion matrix', ...
Daniel@0 26 'NumberTitle', 'off');
Daniel@0 27
Daniel@0 28 plotmat(C, 'k', 'k', 14);
Daniel@0 29 title(['Classification rate: ' num2str(rate(1)) '%'], 'FontSize', 14);