* add FutureWarning for methods with defaults=3
* add explicit cv values to fix assertion errors
* add tests for catching the FutureWarning
* Write current deprecation version
* Add deprecation in docstring
* change default cv value to None
* change cv from 3 to 5 in the examples
* upgrade doctests
* update doctest in tutorial
* update doctest in cross-validation doc
* fix tests
* add entry to whats new
* address Gael comments
* address Gael comments 2
* fix wrong indentation
* update doc
* add docstring deprecation warning in CV subclasses
* address Andy's comments
* fix PR number
* fix flake8
* add filterwarnings in tests
* fix doctests
* cv=None mendatory in Ridge
* fix warning related errors
* skip some doctests warnings
* make travis happy
* change from deprecated to versionchanged
* fix doctests and remove skipping
* address comments
Skeleton for a glossary of concepts and API elements.
This responds to at least three issues:
* Many aspects of scikit-learn API for users and developers are known
tacitly by core contributors (and the stack overflow crowd), but are
not written down in a consistent place.
* What is written is in an ad-hoc narrative style which may be useful
for introduction, but is difficult to refer to and to maintain.
* Parameters such as `n_jobs` and methods like `decision_function` are
described repeatedly in documentation giving sometimes more sometimes
less information. This glossary allows us to use "See :term:`the
glossary <n_jobs>`." so that parameter descriptions in the
API reference can remain brief (just as not every numpy operation
needs to describe broadcasting).
* Fix Rouseeuw1984 broken link
* Change label vbgmm to bgmm
Previously modified with PR #6651
* Change tag name
Old refers to new tag added with PR #7388
* Remove prefix underscore to match tag
* Realign to fit 80 chars
* Link to metrics.rst.
pairwise metrics yet to be documented
* Remove tag as LSHForest is deprecated
* Remove all references to randomized_l1 and sphx_glr_auto_examples_linear_model_plot_sparse_recovery.py.
It is deprecated.
* Fix few Sphinx warnings
* Realign to 80 chars
* Changes based on PR review
* Remove unused ref in calibration
* Fix link ref in covariance.rst
* Fix linking issues
* Differentiate Rouseeuw1999 tag within file.
* Change all duplicate Rouseeuw1999 tags
* Remove numbers from tag Rousseeuw
* remove stuff to be removed 0.19
* more changes
* remove classes from 0.19 whatsnew
* remove _LearntSelectorMixin
* remove ProjectedGradientNMF, load_lwf_*
* minor fixes
* remove more copy from logistic regression path
* remove lda, qda from __init__.__all__
* remove pg solver in nmf from tests etc
* remove class_weight="auto" from tests
* doctest change for decision_function_shape="ovr"
* remove transfrom from tree test, minor fixes to tree tests
* some fixes in the tests
* undo changes in functions which still allow 1d input...
* also allow 1d in scale
* more test fixes...
* last test fixes in forest and tree
* svm default value change doctest failures
* pep8
* remove more class_weight="auto" stuff
* minor cosmetics in docstrings deprecated / removed behavior.
* say that store_covariance has been moved to __init__ in discriminant_analysis
* Update tutorial.rst
* Update tutorial.rst
* Update tutorial.rst
* Update tutorial.rst
* Update index.rst
* Update index.rst
* Update tutorial.rst
* Update tutorial.rst
* Update tutorial.rst
* Update faq.rst
* Update faq.rst
* Divided in two cases (standard columnar and misc data)
I also added a preprocessing note at the end
* Update tutorial.rst
* Update faq.rst
* Update index.rst
Also added some references that were in the original FAQ and pointed the FAQ to here
* Update index.rst
Added the information from the removed part of the FAQ because I felt that the FAQ version was better than the explanation I gave.
* Update index.rst
reference to skimage and also has sklearn.preprocessing.OneHotEncoder instead of OneHotEncoder
* Update index.rst
* Update index.rst
Changed with @jnothman's feedback
d16ac523ed
* Update faq.rst
* optimized file formats added to datasets/index.rst
Note: if you manage your own numerical data it is recommended to use an optimized file format such as HDF5 to reduce data load times. Various libraries such as H5Py, PyTables and pandas provides a Python interface for reading and writing data in that format.
- From the FAQ
* faq.rst: Moved the comment in bunch section to datasets index
This comment has been moved to the datasets index in the external_datasets section:
Note: if you manage your own numerical data it is recommended to use an optimized file format such as HDF5 to reduce data load times. Various libraries such as H5Py, PyTables and pandas provides a Python interface for reading and writing data in that format.
* Update index.rst
Included all changes mentioned by @amueller and @jnothman
* Update faq.rst
* Update faq.rst
* DOC add info to conventions for multi-label fitting
* DOC move to multilabel section and small edits
* DOC clean multilabel examples and clean information
* DOC fix line lengths for multiclass
Nicolas Hug
Hanmin Qin