Why do you want to put a random forest in a numpy array in the first place?
Best,
Gilles
On 26 May 2014 13:11, Lars Buitinck <[email protected]> wrote:
> 2014-05-24 0:28 GMT+02:00 Steven Kearnes <[email protected]>:
> > a is a list of the individual DecisionTreeClassifier objects belonging to
> > the model, instead of a list containing the model itself. The same result
> > occurs if I add dtype=object to np.asarray.
> >
> > Why is this happening? Is there a way to prevent it?
>
> It's because a random forest is an ensemble model and ensemble models
> behave like lists:
>
> >>> len(estimator)
> 10
> >>> estimator[0]
> DecisionTreeClassifier(compute_importances=None, criterion='gini',
> max_depth=None, max_features='auto', max_leaf_nodes=None,
> min_density=None, min_samples_leaf=1, min_samples_split=2,
> random_state=1854205873, splitter='best')
>
> NumPy picks this up and acts accordingly: asarray, when given a
> sequence of things, makes an array of the elements of the sequence.
>
> This behavior was introduced in
> https://github.com/scikit-learn/scikit-learn/commit/7bd3f88f. I don't
> see an easy way to turn this off with modifying the library code.
>
>
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