Rev | Line | |
---|
[80] | 1 | %IRIS 150 objects with 4 features in 3 classes |
---|
| 2 | % |
---|
| 3 | % A = IRIS |
---|
| 4 | % |
---|
| 5 | % Iris plants dataset by R.A.Fisher, 150 objects, 4 features, 3 |
---|
| 6 | % classes. |
---|
[129] | 7 | function x = iris |
---|
[80] | 8 | |
---|
[127] | 9 | prdatasets(mfilename,1,'http://prtools.tudelft.nl/prdatasets/iris.dat'); |
---|
[80] | 10 | user.desc = 'Iris Plant database from UCI. A classic dataset in the pattern recognition literature. The original dataset is a multiclass classification problem, introduced by R.A. Fisher, The use of multiple measurements in taxonomic problems. Ann Eugenics, 7:179--188, 1936.'; |
---|
| 11 | user.link = 'ftp://ftp.ics.uci.edu/pub/machine-learning-databases/iris/'; |
---|
| 12 | cl = {'Iris-setosa' 'Iris-versicolor' 'Iris-virginica'}; |
---|
| 13 | fl = {'sepal length' 'sepal width' 'petal length' 'petal width'}; |
---|
| 14 | |
---|
| 15 | % the fuzzy toolbox has a iris.dat file too, avoid it |
---|
| 16 | pp = fileparts(which(mfilename)); |
---|
| 17 | a = load(fullfile(pp,'iris.dat')); |
---|
[81] | 18 | x = pr_dataset(a(:,1:(end-1)), cl(a(:,end))); |
---|
[80] | 19 | x = setfeatlab(x,fl); |
---|
| 20 | x = setuser(x,user); |
---|
| 21 | x = setname(x,'Iris'); |
---|
| 22 | |
---|
| 23 | return |
---|
Note: See
TracBrowser
for help on using the repository browser.