FWIW, argsort in pure Python is possible given some list l with:
sorted(range(len(l)), key=l.__getitem__)
Sorting by best score would be:
sorted(range(len(l)), key=lambda ind: l[ind].best_score_)
On 27 May 2014 07:39, Steven Kearnes <[email protected]> wrote:
> Thanks for your responses. I've been using a workaround similar to Joel's
> suggestion in the meantime, and it sounds like I just have to stick with
> that for now. Essentially I'm doing a hyperparameter grid search, but in a
> context that doesn't support GridSearchCV, so I'm dealing with multiple
> independent models and had been appending them to a list and then
> converting them to a numpy array for sorting with an argsort derived from
> the scores.
>
>
> On Mon, May 26, 2014 at 4:21 AM, Joel Nothman <[email protected]>wrote:
>
>> It's possible to put a sequence as an object into an array, but you
>> cannot do it with asarray or array directly. Use, for example:
>>
>> a = np.empty(1)
>> a[0] = estimator
>> # alternatively:
>> a[:] = [estimator]
>>
>>
>> On 26 May 2014 21:17, Gilles Louppe <[email protected]> wrote:
>>
>>> 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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