[142] | 1 | %ARCENE Cancer recognition based on mass spectra
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| 2 | %PRTools UCI dataset import, 100+100+700 objects, 10000 features, 2 classes
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| 3 | %
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| 4 | % [TRAIN,VALID,TEST] = ARCENE
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| 5 | % TRAIN_VALID = ARCENE
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| 6 | %
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| 7 | %DESCRIPTION
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| 8 | %This command downloads one of the UCI data sets, converts it into PRTools
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| 9 | %format and stores it locally for future use. Consult the <a href="http://archive.ics.uci.edu/ml/datasets/Arcene">related website</a>.
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| 10 | %for further information. Please make the appropriate references in
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| 11 | %publications that make use of this dataset.
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| 12 | %
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| 13 | %The training set (100 objects) and the validation set (100 objects) are
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| 14 | %labeled. The test set (700 objects) is unlabeled. The order of the
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| 15 | %original feature (spectral bands) is randomized. Moreover, the set is
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| 16 | %merged with a large number of random features. See the dataset <a href="http://archive.ics.uci.edu/ml/datasets/Arcene">website</a>.
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| 17 | %
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[150] | 18 | %SEE ALSO <a href="http://prtools.tudelft.nl/prtools/">PRTools Guide</a>, <a href="http://archive.ics.uci.edu/ml/">UCI Website</a>
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[142] | 19 | %PRTOOLS, DATASETS
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| 20 |
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[150] | 21 | % Copyright: R.P.W. Duin
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[142] | 22 |
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| 23 | function [a,b,c] = arcene
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| 24 |
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| 25 | datfiles = {'ARCENE/arcene_train.data','ARCENE/arcene_valid.data','ARCENE/arcene_test.data'};
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| 26 | labfiles = {'ARCENE/arcene_train.labels','arcene_valid.labels',0};
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| 27 | % use old call
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| 28 | [a,b,c] = pr_download_uci('Arcene',datfiles,[],[],[3,3,18],[],[],' ',labfiles);
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| 29 | c = setlablist(c,[]);
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| 30 |
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| 31 | if nargout < 2
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| 32 | a = [a;b];
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| 33 | a = setname(a,'Arcene Mass Spectra');
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| 34 | end
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| 35 |
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| 36 |
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| 37 |
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