Looks good to me - save the output to a file (e.g. foobar.dot) and run
the following command:
$ dot -Tpdf foobar.dot -o foobar.pdf
When I open the pdf all labels are correctly displayed - remember that
they are not indicator features - so the thresholds are usually
"country=AU <= 0.5".
You can find more information here:
http://scikit-learn.org/dev/modules/tree.html#classification
2013/2/27 David Montgomery <[email protected]>:
> Thanks I used DictVectorizer()
>
> I am now trying to add lables to the tree graph. Below are the labels and
> the digraph Tree. However, I dont see lables on the tree nodes. Did I not
> use feature names correct?
>
>
>
>
> measurements = [
> {'country':'US','city': 'Dubai'},
> {'country':'US','city': 'London'},
> {'country':'US','city': 'San Fransisco'},
> {'country':'US','city': 'Dubai'},
> {'country':'AU','city': 'Mel'},
> {'country':'AU','city': 'Sydney'},
> {'country':'AU','city': 'Mel'},
> {'country':'AU','city': 'Sydney'},
> {'country':'AU','city': 'Mel'},
> {'country':'AU','city': 'Sydney'},
> ]
> y = [0,0,0,1,1,1,1,1,1,1]
>
>
> vec = DictVectorizer()
> X = vec.fit_transform(measurements)
> feature_name = vec.get_feature_names()
> clf = tree.DecisionTreeRegressor()
> clf = clf.fit(X.todense(), y)
> with open("au.dot", 'w') as f:
> f = tree.export_graphviz(clf, out_file=f,feature_names=feature_name)
>
>
> feature_name = ['city=Dubai', 'city=London', 'city=Mel', 'city=San
> Fransisco', 'city=Sydney', 'country=AU', 'country=US']
>
> digraph Tree {
> 0 [label="country=AU <= 0.5000\nerror = 2.1\nsamples = 10\nvalue = [ 0.7]",
> shape="box"] ;
> 1 [label="city=Dubai <= 0.5000\nerror = 0.75\nsamples = 4\nvalue = [ 0.25]",
> shape="box"] ;
> 0 -> 1 ;
> 2 [label="error = 0.0000\nsamples = 2\nvalue = [ 0.]", shape="box"] ;
> 1 -> 2 ;
> 3 [label="error = 0.5000\nsamples = 2\nvalue = [ 0.5]", shape="box"] ;
> 1 -> 3 ;
> 4 [label="error = 0.0000\nsamples = 6\nvalue = [ 1.]", shape="box"] ;
> 0 -> 4 ;
> }
>
>
>
>
> On Wed, Feb 27, 2013 at 9:50 PM, Peter Prettenhofer
> <[email protected]> wrote:
>>
>> Hi David,
>>
>> I recommend that you load the data using Pandas (``pandas.read_csv``).
>> Scikit-learn does not support categorical features out-of-the-box; you
>> need to encode them as dummy variables (aka one-hot encoding) - you
>> can do this either using ``sklearn.preprocessing.DictVectorizer`` or
>> via ``pandas.get_dummies`` .
>>
>> HTH,
>> Peter
>>
>> 2013/2/27 David Montgomery <[email protected]>:
>> > Hi,
>> >
>> > I have a data structure that looks like this:
>> >
>> > 1 NewYork 1 6 high
>> > 0 LA 3 4 low
>> > .......
>> >
>> > I am trying to predict probability where Y is column one. The all of
>> > the
>> > attributes of the X are categorical and I will use a dtree regression.
>> > How
>> > do I load this data into the y and X?
>> >
>> > Thanks
>> >
>> >
>> > ------------------------------------------------------------------------------
>> > Everyone hates slow websites. So do we.
>> > Make your web apps faster with AppDynamics
>> > Download AppDynamics Lite for free today:
>> > http://p.sf.net/sfu/appdyn_d2d_feb
>> > _______________________________________________
>> > Scikit-learn-general mailing list
>> > [email protected]
>> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>> >
>>
>>
>>
>> --
>> Peter Prettenhofer
>>
>>
>> ------------------------------------------------------------------------------
>> Everyone hates slow websites. So do we.
>> Make your web apps faster with AppDynamics
>> Download AppDynamics Lite for free today:
>> http://p.sf.net/sfu/appdyn_d2d_feb
>> _______________________________________________
>> Scikit-learn-general mailing list
>> [email protected]
>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
>
> ------------------------------------------------------------------------------
> Everyone hates slow websites. So do we.
> Make your web apps faster with AppDynamics
> Download AppDynamics Lite for free today:
> http://p.sf.net/sfu/appdyn_d2d_feb
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
--
Peter Prettenhofer
------------------------------------------------------------------------------
Everyone hates slow websites. So do we.
Make your web apps faster with AppDynamics
Download AppDynamics Lite for free today:
http://p.sf.net/sfu/appdyn_d2d_feb
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
