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).
* 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
Passing 1D arrays to check_array, without setting `ensure_2d` to false now
raises a deprecation warning before reshaping it. This will later throw an
error.
All Scaler classes also throw warnings when 1D arrays are passed.
All unit tests/doctests are modified to ensure that no 1D arrays are passed,
except in explicit 1D array tests where the warnings have been silenced.
Additional tests are also included which check for different 1D array cases.
2D array tests with one samples and one features are also added and where
they failed, `check_array` call has been modified to give a more useful error
message
Chiara Marmo
Hanmin Qin