8000 DOC Fix typos, via a Levenshtein-style corrector (#15923) · scikit-learn/scikit-learn@0e10b3a · GitHub
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DOC Fix typos, via a Levenshtein-style corrector (#15923)
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azure-pipelines.yml

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# It runs tests requiring pandas and PyAMG.
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pylatest_pip_openblas_pandas:
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DISTRIB: 'conda-pip-latest'
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# FIXME: pinned until SciPy wheels are available for Pyhon 3.8
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# FIXME: pinned until SciPy wheels are available for Python 3.8
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PYTHON_VERSION: '3.8'
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PYTEST_VERSION: '4.6.2'
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COVERAGE: 'true'

benchmarks/bench_plot_randomized_svd.py

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# in case the reconstructed (dense) matrix is too large
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MAX_MEMORY = np.int(2e9)
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# The following datasets can be dowloaded manually from:
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# The following datasets can be downloaded manually from:
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# CIFAR 10: https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
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# SVHN: http://ufldl.stanford.edu/housenumbers/train_32x32.mat
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CIFAR_FOLDER = "./cifar-10-batches-py/"

benchmarks/bench_text_vectorizers.py

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text = fetch_20newsgroups(subset='train').data[:1000]
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print("="*80 + '\n#' + " Text vectorizers benchmark" + '\n' + '='*80 + '\n')
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print("Using a subset of the 20 newsrgoups dataset ({} documents)."
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print("Using a subset of the 20 newsgroups dataset ({} documents)."
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.format(len(text)))
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print("This benchmarks runs in ~1 min ...")
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build_tools/azure/install.sh

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version_ge() {
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# The two version numbers are separated with a new line is piped to sort
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# -rV. The -V activates for version number sorting and -r sorts in
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# decending order. If the first argument is the top element of the sort, it
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# descending order. If the first argument is the top element of the sort, it
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# is greater than or equal to the second argument.
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test "$(printf "${1}\n${2}" | sort -rV | head -n 1)" == "$1"
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}

doc/developers/advanced_installation.rst

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If you plan on submitting a pull-request, you should clone from your fork
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instead.
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#. Install a compiler with OpenMP_ support for your platform. See intructions
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#. Install a compiler with OpenMP_ support for your platform. See instructions
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for :ref:`compiler_windows`, :ref:`compiler_macos`, :ref:`compiler_linux`
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and :ref:`compiler_freebsd`.
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doc/developers/contributing.rst

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methods available in scikit-learn.
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10. New features often need to be illustrated with narrative documentation in
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the user guide, with small code snipets. If relevant, please also add
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the user guide, with small code snippets. If relevant, please also add
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references in the literature, with PDF links when possible.
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11. The user guide should also include expected time and space complexity

doc/developers/maintainer.rst

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2. On the branch for releasing, update the version number in
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sklearn/__init__.py, the ``__version__`` variable by removing ``dev*`` only
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when ready to release.
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On master, increment the verson in the same place (when branching for
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On master, increment the version in the same place (when branching for
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release).
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3. Create the tag and push it::

doc/glossary.rst

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TODO: `This gist
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<https://gist.github.com/jnothman/4807b1b0266613c20ba4d1f88d0f8cf5>`_
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higlights the use of the different formats for multilabel.
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highlights the use of the different formats for multilabel.
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multioutput classification
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A list of 2d arrays, corresponding to each multiclass decision
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function.

doc/modules/clustering.rst

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considered an outlier by the algorithm.
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While the parameter ``min_samples`` primarily controls how tolerant the
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algorithm is towards noise (on noisy and large data sets it may be desiable
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algorithm is towards noise (on noisy and large data sets it may be desirable
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to increase this parameter), the parameter ``eps`` is *crucial to choose
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appropriately* for the data set and distance function and usually cannot be
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left at the default value. It controls the local neighborhood of the points.

doc/themes/scikit-learn-modern/javascript.html

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prevScrollpos = lastScrollTop;
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};
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/*** high preformance scroll event listener***/
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/*** high performance scroll event listener***/
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var raf = window.requestAnimationFrame ||
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window.webkitRequestAnimationFrame ||
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window.mozRequestAnimationFrame ||

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