Last change
on this file since 45 was
20,
checked in by bduin, 13 years ago
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updates for handling soft labels
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File size:
943 bytes
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1 | %ISSQUARE Test on square dissimilarity matrix
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2 | %
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3 | % OK = ISSQUARE(D)
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4 | % ISSQUARE(D)
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5 | %
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6 | % INPUT
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7 | % D Dataset
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8 | %
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9 | % OUTPUT
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10 | % OK 1 if the matrix D is square and 0, otherwise.
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11 | %
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12 | % DESCRIPTION
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13 | % True is D is a square dissimilarity matrix dataset. This includes
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14 | % the check (in case of crisp dataset D) whether feature labels equal
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15 | % object labels. If called without an output argument ISSQUARE generates an
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16 | % error if D is not square.
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17 |
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18 | % Copyright: Elzbieta Pekalska, ela.pekalska@googlemail.com
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19 | % Faculty EWI, Delft University of Technology and
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20 | % School of Computer Science, University of Manchester
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21 |
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22 |
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23 | function OK = issquare(d)
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24 | isdataset(d);
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25 | [m,k] = size(d);
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26 |
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27 | if m == k
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28 | if islabtype(d,'crisp')
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29 | n = nlabcmp(getfeatlab(d),getlabels(d));
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30 | OK = (n == 0);
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31 | else
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32 | OK = 1;
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33 | end
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34 | else
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35 | OK = 0;
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36 | end
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37 |
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38 | if nargout == 0 & OK == 0
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39 | error([newline '---- Square dissimilarity matrix expected ----'])
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40 | end
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