| [80] | 1 | %AUTO_MPG Car/miles-per-gallon, 398 objects, 6 features, 2 classes |
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| 2 | % |
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| 3 | % A = AUTO_MPG |
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| 4 | % |
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| 5 | % Load the dataset in A. This is the 'auto-mpg' dataset of the UCI |
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| 6 | % Machine Learning Repository, //www.ics.uci.edu/~mlearn/MLRepository.html |
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| 7 | % |
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| [124] | 8 | % There are two classes: 229 objects < 25 mpg and 169 objects > 25 mpg. |
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| 9 | % For some reasons one of the original features is missing (horsepower). |
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| 10 | % |
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| [80] | 11 | % See also DATASETS, PRDATASETS |
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| 12 | |
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| [132] | 13 | % Copyright: R.P.W. Duin |
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| [80] | 14 | % Faculty EWI, Delft University of Technology |
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| 15 | % P.O. Box 5031, 2600 GA Delft, The Netherlands |
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| 16 | |
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| 17 | % $Id: auto_mpg.m,v 1.1.1.1 2003/05/16 11:20:35 bob Exp $ |
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| 18 | |
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| [119] | 19 | function a = auto_mpg |
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| [132] | 20 | a = pr_getdata('http://prtools.tudelft.nl/prdatasets/auto_mpg.mat',1); |
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| [124] | 21 | %a = setname(a,'Car-miles-per-gallon'); |
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| [122] | 22 | a = setlablist(a,char('< 25 mpg ','> 25 mpg')); |
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| 23 | a = setfeatlab(a,char(... |
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| [80] | 24 | 'cylinders: multi-valued discrete', ... |
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| 25 | 'displacement: continuous', ... |
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| 26 | 'weight: continuous', ... |
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| 27 | 'acceleration: continuous', ... |
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| [124] | 28 | 'model year: multi-valued discrete', ... |
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| 29 | 'origin: multi-valued discrete')); |
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