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1 | %ECOLI 336 objects with 7 features in 8 classes |
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2 | % |
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3 | % X = ECOLI |
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4 | % |
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5 | % Predict the localization site of protein in a cell, by Kenta Nakai |
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6 | % Institue of Molecular and Cellular Biology Osaka, University |
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7 | % This is the 'Ecoli' dataset of the UCI Machine Learning Repository, |
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8 | % //www.ics.uci.edu/~mlearn/MLRepository.html |
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9 | |
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10 | function a = ecoli |
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11 | |
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12 | a = pr_loadmatfile; |
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13 | if isempty(a) |
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14 | opt.labfeat = 8; |
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15 | opt.featnames = {'mcg' 'gvh' 'lip' 'chg' 'aac' 'alm1' 'alm2'}; |
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16 | opt.classnames = {'cytoplasm' 'inner membrane without signal sequence' ... |
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17 | 'periplasm' 'inner membrane, uncleavable signal sequence' ... |
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18 | 'outer membrane' 'outer membrane lipoprotein' ... |
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19 | 'inner membrane lipoprotein' 'inner membrane, cleavable signal sequence'}; |
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20 | opt.desc='The Ecoli database from UCI. Goal is to Predict the localization site of protein in a cell, by Kenta Nakai Institue of Molecular and Cellular Biology Osaka, University.'; |
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21 | opt.link = 'ftp://ftp.ics.uci.edu/pub/machine-learning-databases/ecoli/'; |
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22 | opt.dsetname = 'Ecoli Dataset'; |
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23 | a = pr_download('http://prtools.tudelft.nl/prdatasets/ecoli.dat',[],opt); |
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24 | end |
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25 | |
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26 | return |
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