[scikit-learn] Why do DTs have a different fit protocol than NB and SVMs?
stuart at stuartreynolds.net
Tue Dec 13 15:33:48 EST 2016
I think he's asking whether returning the model is part of the API (i.e. is
it a bug that SVM and NB don't return self?).
On Tue, Dec 13, 2016 at 12:23 PM, Jacob Schreiber <jmschreiber91 at gmail.com>
> The fit method returns the object itself, so regardless of which way you
> do it, it will work. The reason the fit method returns itself is so that
> you can chain methods, like "preds = clf.fit(X, y).predict(X)"
> On Tue, Dec 13, 2016 at 12:14 PM, Graham Arthur Mackenzie <
> graham.arthur.mackenzie at gmail.com> wrote:
>> Hello All,
>> I hope this is the right way to ask a question about documentation.
>> In the doc for Decision Trees
>> <http://scikit-learn.org/stable/modules/tree.html#tree>, the fit
>> statement is assigned back to the classifier:
>> clf = clf.fit(X, Y)
>> Whereas, for Naive Bayes
>> and Support Vector Machines
>> it's just:
>> clf.fit(X, Y)
>> I assumed this was a typo, but thought I should try and verify such
>> before proceeding under that assumption. I appreciate any feedback you can
>> Thank You and Be Well,
>> scikit-learn mailing list
>> scikit-learn at python.org
> scikit-learn mailing list
> scikit-learn at python.org
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