Register OneVsRestRegressor as meta estimator Rename to a more sensible name Parallel predict and sparse support Started MultiOutput documentation Move code to new file multioutput.py Continuing the move to new multioutput module Added sample weight support Better test for sample weights and actually support weights Added a new test using weighted vs repeated samples to test sample weight support. Uncovered that weights were not actually passed on to underlying estimator. Comment on multiprocess overheads Move parallel_helper to utils.fixes This helper works around a python2 limitation on pickling instance methods Example of multi-output regression with gradient boosting Switch to uniform weighted score and updated example The example now uses a RF with and without the MultiOutput meta estimator Added note for removing `score` method Addressing comments on MultiOutputRegressor MultiOutputregressor better test for weighted samples Fix ups Use explicit keyword argument for passing sample weights and fix random_state on train-test split in the example |
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| datasets | ||
| developers | ||
| images | ||
| includes | ||
| logos | ||
| modules | ||
| sphinxext | ||
| templates | ||
| testimonials | ||
| themes/scikit-learn | ||
| tutorial | ||
| Makefile | ||
| README | ||
| about.rst | ||
| conf.py | ||
| data_transforms.rst | ||
| documentation.rst | ||
| faq.rst | ||
| index.rst | ||
| install.rst | ||
| make.bat | ||
| model_selection.rst | ||
| preface.rst | ||
| presentations.rst | ||
| related_projects.rst | ||
| supervised_learning.rst | ||
| support.rst | ||
| tune_toc.rst | ||
| unsupervised_learning.rst | ||
| user_guide.rst | ||
| whats_new.rst | ||
README
Documentation for scikit-learn
-------------------------------
This section contains the full manual and web page as displayed in
http://scikit-learn.org. To generate the full web page, including
the example gallery (this might take a while):
make html
Or, if you'd rather not build the example gallery:
make html-noplot
That should create all the doc in directory _build/html
To build the PDF manual, run
make latexpdf
The website is hosted at github and can be updated manually (for releases)
by pushing to the https://github.com/scikit-learn/scikit-learn.github.io repository.
It's recommended to run OptiPNG, before uploading the website.
The PNG files generated by Matplotlib tend to be ~20% too big, and they're
costing us bandwidth. You can run OptiPNG with::
make optipng
Development documentation automated build
-----------------------------------------
A Rackspace cloud server named 'docbuilder' is continuously building the master branch
to update the http://scikit-learn.org/dev tree of the website.
The configuration of this server is managed at:
http://github.com/scikit-learn/sklearn-docbuilder