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Merge tag '0.19b2' into releases
Release 0.19b2 * tag '0.19b2': (808 commits) Preparing 0.19b2 [MRG+1] FIX out of bounds array access in SAGA (scikit-learn#9376) FIX make test_importances pass on 32 bit linux Release 0.19b1 DOC remove 'in dev' header in whats_new.rst DOC typos in whats_news.rst [ci skip] [MRG] DOC cleaning up what's new for 0.19 (scikit-learn#9252) FIX t-SNE memory usage and many other optimizer issues (scikit-learn#9032) FIX broken link in gallery and bad title rendering [MRG] DOC Replace \acute by prime (scikit-learn#9332) Fix typos (scikit-learn#9320) [MRG + 1 (rv) + 1 (alex) + 1] Add a check to test the docstring params and their order (scikit-learn#9206) DOC Residual sum vs. regression sum (scikit-learn#9314) [MRG] [HOTFIX] Fix capitalization in test and hence fix failing travis at master (scikit-learn#9317) More informative error message for classification metrics given regression output (scikit-learn#9275) [MRG] COSMIT Remove unused parameters in private functions (scikit-learn#9310) [MRG+1] Ridgecv normalize (scikit-learn#9302) [MRG + 2] ENH Allow `cross_val_score`, `GridSearchCV` et al. to evaluate on multiple metrics (scikit-learn#7388) Add data_home parameter to fetch_kddcup99 (scikit-learn#9289) FIX makedirs(..., exists_ok) not available in Python 2 (scikit-learn#9284) ...
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comment: off
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coverage:
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status:
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project:
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default:
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# Commits pushed to master should not make the overall
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# project coverage decrease by more than 1%:
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target: auto
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threshold: 1%
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patch:
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default:
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# Be tolerant on slight code coverage diff on PRs to limit
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# noisy red coverage status on github PRs.
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# Note The coverage stats are still uploaded
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# to codecov so that PR reviewers can see uncovered lines
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# in the github diff if they install the codecov browser
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# extension:
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# https://github.com/codecov/browser-extension
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target: auto
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threshold: 1%
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/sklearn/__check_build/_check_build.c -diff
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/sklearn/_isotonic.c -diff
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/sklearn/cluster/_dbscan_inner.cpp -diff
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/sklearn/cluster/_hierarchical.cpp -diff
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/sklearn/cluster/_k_means.c -diff
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/sklearn/cluster/_k_means_elkan.c -diff
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/sklearn/datasets/_svmlight_format.c -diff
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/sklearn/decomposition/_online_lda.c -diff
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/sklearn/decomposition/cdnmf_fast.c -diff
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/sklearn/ensemble/_gradient_boosting.c -diff
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/sklearn/feature_extraction/_hashing.c -diff
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/sklearn/linear_model/cd_fast.c -diff
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/sklearn/linear_model/sgd_fast.c -diff
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/sklearn/linear_model/sag_fast.c -diff
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/sklearn/metrics/pairwise_fast.c -diff
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/sklearn/neighbors/ball_tree.c -diff
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/sklearn/neighbors/kd_tree.c -diff
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/sklearn/svm/liblinear.c -diff
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/sklearn/svm/libsvm.c -diff
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/sklearn/svm/libsvm_sparse.c -diff
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/sklearn/tree/_tree.c -diff
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/sklearn/tree/_utils.c -diff
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/sklearn/utils/arrayfuncs.c -diff
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/sklearn/utils/graph_shortest_path.c -diff
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/sklearn/utils/lgamma.c -diff
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/sklearn/utils/_logistic_sigmoid.c -diff
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/sklearn/utils/murmurhash.c -diff
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/sklearn/utils/seq_dataset.c -diff
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/doc/whats_new.rst merge=union
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.coverage
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coverage
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*.py,cover
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.tags
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.tags*
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tags
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covtype.data.gz
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20news-18828/
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.pydevproject
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.idea
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cythonize.dat
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*.c
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*.cpp
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!*/src/*.c
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!*/src/*.cpp
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*.sln
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*.pyproj
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# Used by py.test
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.cache
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@@ -23,10 +23,10 @@ Brian Holt <bh00038@cvplws63.eps.surrey.ac.uk> <bdholt1@gmail.com>
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Christian Osendorfer <osendorf@gmail.com>
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Clay Woolam <clay@woolam.org>
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Danny Sullivan <dsullivan7@hotmail.com> <dbsullivan23@gmail.com>
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Denis Engemann <d.engemann@fz-juelich.de>
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Denis Engemann <d.engemann@fz-juelich.de> <denis.engemann@gmail.com>
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Denis Engemann <d.engemann@fz-juelich.de> <dengemann@Deniss-MacBook-Pro.local>
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Denis Engemann <d.engemann@fz-juelich.de> <dengemann <denis.engemann@gmail.com>
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Denis Engemann <denis-alexander.engemann@inria.fr>
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Denis Engemann <denis-alexander.engemann@inria.fr> <denis.engemann@gmail.com>
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Denis Engemann <denis-alexander.engemann@inria.fr> <dengemann@Deniss-MacBook-Pro.local>
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Denis Engemann <denis-alexander.engemann@inria.fr> <dengemann <denis.engemann@gmail.com>
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Diego Molla <dmollaaliod@gmail.com> <diego@diego-desktop.(none)>
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DraXus <draxus@gmail.com> draxus <draxus@hammer.ugr>
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Edouard DUCHESNAY <ed203246@is206877.intra.cea.fr> <duchesnay@is143433.(none)>
@@ -61,7 +61,7 @@ Jake VanderPlas <vanderplas@astro.washington.edu> <jakevdp@gmail.com>
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Jake VanderPlas <vanderplas@astro.washington.edu> <vanderplas@astro.washington.edu>
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James Bergstra <james.bergstra@gmail.com>
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Jaques Grobler <jaques.grobler@inria.fr> <jaquesgrobler@gmail.com>
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Jan Schl�ter <scikit-learn@jan-schlueter.de>
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Jan Schlüter <scikit-learn@jan-schlueter.de>
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Jean Kossaifi <jean.kossaifi@gmail.com>
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Jean Kossaifi <jean.kossaifi@gmail.com> <jkossaifi@is208616.intra.cea.fr>
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Jean Kossaifi <jean.kossaifi@gmail.com> <kossaifi@is208616.intra.cea.fr>
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Olivier Hervieu <olivier.hervieu@gmail.com> <olivier.hervieu@tinyclues.com>
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Paul Butler <paulgb@gmail.com>
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Peter Prettenhofer <peter.prettenhofer@gmail.com>
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Raghav R V <rvraghav93@gmail.com>
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Raghav RV <rvraghav93@gmail.com>
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Raghav RV <rvraghav93@gmail.com> <ragvrv@gmail.com>
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Robert Layton <robertlayton@gmail.com>
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Roman Sinayev <roman.sinayev@gmail.com>
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Roman Sinayev <roman.sinayev@gmail.com> <roman@y570.(none)>
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language: python
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# Pre-install packages for the ubuntu distribution
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cache:
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apt: true
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directories:
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- $HOME/.cache/pip
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- $HOME/download
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addons:
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apt:
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packages:
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- libatlas3gf-base
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- libatlas-dev
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# only required by the DISTRIB="ubuntu" build:
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- python-scipy
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- $HOME/.ccache
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dist: trusty
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env:
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global:
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# Directory where tests are run from
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- TEST_DIR=/tmp/sklearn
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- OMP_NUM_THREADS=4
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- OPENBLAS_NUM_THREADS=4
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matrix:
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# This environment tests that scikit-learn can be built against
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# versions of numpy, scipy with ATLAS that comes with Ubuntu Precise 12.04
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- DISTRIB="ubuntu" PYTHON_VERSION="2.7" CYTHON_VERSION="0.23.4"
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COVERAGE=true
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# This environment tests the oldest supported anaconda env
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- DISTRIB="conda" PYTHON_VERSION="2.6" INSTALL_MKL="false"
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NUMPY_VERSION="1.6.2" SCIPY_VERSION="0.11.0" CYTHON_VERSION="0.23"
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# This environment tests the newest supported anaconda env
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- DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
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NUMPY_VERSION="1.10.4" SCIPY_VERSION="0.17.0" PANDAS_VERSION="0.18.0"
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CYTHON_VERSION="0.23.4"
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# flake8 linting on diff wrt common ancestor with upstream/master
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- RUN_FLAKE8="true" SKIP_TESTS="true"
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DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
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NUMPY_VERSION="1.10.4" SCIPY_VERSION="0.17.0" CYTHON_VERSION="0.23.4"
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# We are using this to allow failures for DISTRIB=scipy-dev-wheels
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# This environment tests that scikit-learn can be built against
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# versions of numpy, scipy with ATLAS that comes with Ubuntu Trusty 14.04
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- env: DISTRIB="ubuntu" PYTHON_VERSION="2.7" CYTHON_VERSION="0.23.4"
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addons:
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apt:
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packages:
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# these only required by the DISTRIB="ubuntu" builds:
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- python-scipy
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- libatlas3gf-base
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- libatlas-dev
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# This environment tests the oldest supported anaconda env
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- env: DISTRIB="conda" PYTHON_VERSION="2.7" INSTALL_MKL="false"
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NUMPY_VERSION="1.8.2" SCIPY_VERSION="0.13.3" CYTHON_VERSION="0.23.5"
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COVERAGE=true
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# This environment tests the newest supported Anaconda release (4.4.0)
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# It also runs tests requiring Pandas.
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- env: DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
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NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0" PANDAS_VERSION="0.20.1"
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CYTHON_VERSION="0.25.2" COVERAGE=true
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# This environment use pytest to run the tests. It uses the newest
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# supported Anaconda release (4.4.0). It also runs tests requiring Pandas.
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- env: USE_PYTEST="true" DISTRIB="conda" PYTHON_VERSION="3.6.1"
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INSTALL_MKL="true" NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0"
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PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"
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# flake8 linting on diff wrt common ancestor with upstream/master
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- env: RUN_FLAKE8="true" SKIP_TESTS="true"
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DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
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NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0" CYTHON_VERSION="0.23.5"
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TEST_DOCSTRINGS="true"
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# https://github.com/travis-ci/apt-package-whitelist/issues/2407
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- python: 3.5
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Please do not email the authors directly to ask for assistance or report issues.
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Instead, please see `What's the best way to ask questions about scikit-learn
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<http://scikit-learn.org/stable/faq.html#what-s-the-best-way-to-ask-questions-about-scikit-learn>`_
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<http://scikit-learn.org/stable/faq.html#what-s-the-best-way-to-get-help-on-scikit-learn-usage>`_
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in the FAQ.
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**Note: This document is a 'getting started' summary for contributing code,
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page**](http://scikit-learn.org/stable/developers/contributing.html)
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for the full contributor's guide. Please read it carefully to help make
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the code review process go as smoothly as possible and maximize the
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likelihood of your contribution being merged.**
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likelihood of your contribution being merged.
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How to contribute
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-----------------
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The preferred workflow for contributing to scikit-learn is to fork the
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a copy of the code under your GitHub user account.
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a copy of the code under your GitHub user account. For more details on
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how to fork a repository see [this guide](https://help.github.com/articles/fork-a-repo/).
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Pull Request Checklist
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Incomplete contributions should be prefixed `[WIP]` (to indicate a work
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Two core developers will review your code and change the prefix of the pull
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request to `[MRG + 1]` and `[MRG + 2]` on approval, making it eligible
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for merging. An incomplete contribution -- where you expect to do more work before
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receiving a full review -- should be prefixed `[WIP]` (to indicate a work
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functionality is useful in practice and, if possible, compare it
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- Documentation and high-coverage tests are necessary for enhancements
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- Documentation and high-coverage tests are necessary for enhancements to be
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accepted. Bug-fixes or new features should be provided with
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[non-regression tests](https://en.wikipedia.org/wiki/Non-regression_testing).
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These tests verify the correct behavior of the fix or feature. In this
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manner, further modifications on the code base are granted to be consistent
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with the desired behavior.
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For the Bug-fixes case, at the time of the PR, this tests should fail for
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as your Python, scikit-learn, numpy, and scipy versions. This information
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can be found by runnning the following code snippet:
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can be found by running the following code snippet:
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[reproducible](http://stackoverflow.com/help/mcve) code snippet
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[matplotlib](http://matplotlib.sourceforge.net/), and
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[matplotlib](http://matplotlib.org/), and
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[pillow](http://pillow.readthedocs.io/en/latest/).
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-------------------
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section of the website for more information including conforming to the
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New BSD License
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Copyright (c) 2007–2016 The scikit-learn developers.
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Copyright (c) 2007–2017 The scikit-learn developers.
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All rights reserved.
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#### Steps/Code to Reproduce
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<!--
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Example:
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```
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```python
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# make tags for symbol based navigation in emacs and vim