_)
> I have to confirm that with more classes.
>
> Regards
> Gregory
>
> De : scikit-learn de la
> part de Sebastian Raschka
> Envoyé : lundi 24 octobre 2016 17:47
> À : Scikit-learn user and developer mailing list
> Objet : Re: [scikit-learn] tree visualization with class
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 P
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 s
gards
Gregory
De : scikit-learn de la
part de Sebastian Raschka
Envoyé : lundi 24 octobre 2016 17:47
À : Scikit-learn user and developer mailing list
Objet : Re: [scikit-learn] tree visualization with class names in leaves
Hi, Greg,
if you provide the `class_names` argument, a “class
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 -> ‘set
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
