[scikit-learn] tree visualization with class names in leaves

[Startup Hire]

Hi Piotr,

Thanks for the reply.

I understand the thresholds at the current node.

I was referring to this:

Consider the node: Duration <= 0.5 having gini = 0.3386 and samples =
327510      What is meant by this:   value = [216974.9673, 59743.3314]

Regards,
Sanant

On Tue, Oct 25, 2016 at 3:02 PM, Piotr Bialecki <piotr.bialecki at hotmail.de>
wrote:

> Hi Sanant,
>
> the values represent the thresholds at the current feature (node), which
> are used to classify the next sample.
>
> You can see an example here:
> http://scikit-learn.org/stable/modules/tree.html
>
> The first node uses the feature "petal length (cm)" with a threshold of
> 2.45.
>
> If your future sample as a petal length <= 2.45cm it will be pushed into
> the left branch and therefore will be classifies as class = setosa.
> However, if the petal length is > 2.45cm, it will be pushed into the right
> branch and the next node (feature) is evalueted.
>
> I hope I understood your question correct.
>
>
> Best regards,
> Piotr
>
>
>
>
> On 25.10.2016 08:41, Startup Hire wrote:
>
> Hi all,
>
> Thanks for the suggestion.
>
> I have a related question on tree visualization
>
> I have 2 classes to predict: 0 and 1 (it comes up as a numeric field when
> I load the dataset)
>
> I have given the class_names as "NotPresent" and "Ispresent" which I
> believe it will map to 0 and 1. is that correct?
>
>
> How do I interpret the nodes and value present in each nodes in the
> accompanying diagram?
>
> Regards,
> Sanant
>
>
>
>
> On Mon, Oct 24, 2016 at 9:17 PM, Sebastian Raschka <
> <se.raschka at gmail.com>se.raschka at gmail.com> wrote:
>
>> Hi, Greg,
>> if you provide the `class_names` argument, a “class” label of the
>> majority class will be added at the bottom of each node. For instance, if
>> you have the Iris dataset, with class labels 0, 1, 2, you can provide the
>> `class_names` as ['setosa', 'versicolor', 'virginica’], where  0 ->
>> ‘setosa’, 1 -> ‘versicolor’, 2 -> ‘virginica’.
>>
>> Best,
>> Sebastian
>>
>> > On Oct 24, 2016, at 10:18 AM, greg g < <greg315 at hotmail.fr>
>> greg315 at hotmail.fr> wrote:
>> >
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>> >
>> > Hi,
>> >  I just begin with scikit-learn and would like to visualize a
>> classification tree with class names displayed in the leaves as shown in
>> the SCIKITLEARN.TREE documentation http://scikit-learn.org/stable
>> /modules/tree.html where we find class=’virginica’ etc…
>> > I made a tree providing a 2D array X (n1 samples , n2 features) and 1D
>> array Y (n1 corresponding classes ) such that Y(i) is the class of the
>> sample X(i, …)
>> > After that I have correct predictions using predict()
>> > Then I use the function
>> > export_graphviz(clf, out_file=dot_data,feature_names=FEATURES)
>> > with FEATURES being the array of my n2 features names in the same order
>> as in X
>> > I obtain the tree .png but can’t find a way to have the correct class
>> names in the leaves…
>> > In export_graphviz() should I use the class_names optional parameter
>> and how ?
>> > Thanks for any help
>> >
>> > Gregory, Toulouse FRANCE
>> >
>> >
>> >
>> > _______________________________________________
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