[scikit-learn] Issue with DecisionTreeClassifier

[Joel Nothman]

Or just running estimator.tree_.apply(X_train) and inferring from there.

On 30 August 2016 at 13:22, Nelson Liu <nfliu at uw.edu> wrote:

> estimator.tree_.value gives the constant prediction of the tree at each
> node. Think of it as what the tree would output if that node was a leaf.
>
> I don't think we have a readily available way of checking the number of
> training samples of each class in a given tree node. The closest thing
> easily accessible is estimator.tree_.n_node_samples. Getting
> finer-grained counts of the number of samples in each class would require
> modifying the source code, I think.
>
> On Mon, Aug 29, 2016 at 8:06 PM Ibrahim Dalal via scikit-learn <
> scikit-learn at python.org> wrote:
>
>> Hi,
>>
>> What does the estimator.tree_.value array represent? I looked up the
>> source code but not able to get what it is. I am interested in the number
>> of training samples of each class in a given tree node.
>>
>> Thanks
>>
>> On Mon, Aug 29, 2016 at 9:22 PM, Andreas Mueller <t3kcit at gmail.com>
>> wrote:
>>
>>>
>>>
>>> On 08/28/2016 03:23 PM, Nelson Liu wrote:
>>>
>>> That should be:
>>> node indicator = estimator.tree_.decision_path(X_test)
>>>
>>> PR welcome :)
>>>
>>> Was there a reason not to make this a "plot" example?
>>> Would it take too long? Not having run examples by CI is a pretty big
>>> maintenance burden.
>>>
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