Square2rect

Improved error handling

changes from GaelVaroquaux

Multilabel

Update random forest example to demo n_jobs=2

Hmmc

…scikit-learn#7838)

* initial commit for return_std

* initial commit for return_std

* adding tests, examples, ARD predict_std

* adding tests, examples, ARD predict_std

* a smidge more documentation

* a smidge more documentation

* Missed a few PEP8 issues

* Changing predict_std to return_std #1

* Changing predict_std to return_std #2

* Changing predict_std to return_std #3

* Changing predict_std to return_std final

* adding better plots via polynomial regression

* trying to fix flake error

* fix to ARD plotting issue

* fixing some flakes

* Two blank lines part 1

* Two blank lines part 2

* More newlines!

* Even more newlines

* adding info to the doc string for the two plot files

* Rephrasing "polynomial" for Bayesian Ridge Regression

* Updating "polynomia" for ARD

* Adding more formal references

* Another asked-for improvement to doc string.

* Fixing flake8 errors

* Cleaning up the tests a smidge.

* A few more flakes

* requested fixes from Andy

* Mini bug fix

* Final pep8 fix

* pep8 fix round 2

* Fix beta_ to alpha_ in the comments

* resurrect quantile scaler

* move the code in the pre-processing module

* first draft

* Add tests.

* Fix bug in QuantileNormalizer.

* Add quantile_normalizer.

* Implement pickling

* create a specific function for dense transform

* Create a fit function for the dense case

* Create a toy examples

* First draft with sparse matrices

* remove useless functions and non-negative sparse compatibility

* fix slice call

* Fix tests of QuantileNormalizer.

* Fix estimator compatibility

* List of functions became tuple of functions
* Check X consistency at transform and inverse transform time

* fix doc

* Add negative ValueError tests for QuantileNormalizer.

* Fix cosmetics

* Fix compatibility numpy <= 1.8

* Add n_features tests and correct ValueError.

* PEP8

* fix fill_value for early scipy compatibility

* simplify sampling

* Fix tests.

* removing last pring

* Change choice for permutation

* cosmetics

* fix remove remaining choice

* DOC

* Fix inconsistencies

* pep8

* Add checker for init parameters.

* hack bounds and make a test

* FIX/TST bounds are provided by the fitting and not X at transform

* PEP8

* FIX/TST axis should be <= 1

* PEP8

* ENH Add parameter ignore_implicit_zeros

* ENH match output distribution

* ENH clip the data to avoid infinity due to output PDF

* FIX ENH restraint to uniform and norm

* [MRG] ENH Add example comparing the distribution of all scaling preprocessor (#2)

* ENH Add example comparing the distribution of all scaling preprocessor

* Remove Jupyter notebook convert

* FIX/ENH Select feat before not after; Plot interquantile data range for all

* Add heatmap legend

* Remove comment maybe?

* Move doc from robust_scaling to plot_all_scaling; Need to update doc

* Update the doc

* Better aesthetics; Better spacing and plot colormap only at end

* Shameless author re-ordering ;P

* Use env python for she-bang

* TST Validity of output_pdf

* EXA Use OrderedDict; Make it easier to add more transformations

* FIX PEP8 and replace scipy.stats by str in example

* FIX remove useless import

* COSMET change variable names

* FIX change output_pdf occurence to output_distribution

* FIX partial fixies from comments

* COMIT change class name and code structure

* COSMIT change direction to inverse

* FIX factorize transform in _transform_col

* PEP8

* FIX change the magic 10

* FIX add interp1d to fixes

* FIX/TST allow negative entries when ignore_implicit_zeros is True

* FIX use np.interp instead of sp.interpolate.interp1d

* FIX/TST fix tests

* DOC start checking doc

* TST add test to check the behaviour of interp numpy

* TST/EHN Add the possibility to add noise to compute quantile

* FIX factorize quantile computation

* FIX fixes issues

* PEP8

* FIX/DOC correct doc

* TST/DOC improve doc and add random state

* EXA add examples to illustrate the use of smoothing_noise

* FIX/DOC fix some grammar

* DOC fix example

* DOC/EXA make plot titles more succint

* EXA improve explanation

* EXA improve the docstring

* DOC add a bit more documentation

* FIX advance review

* TST add subsampling test

* DOC/TST better example for the docstring

* DOC add ellipsis to docstring

* FIX address olivier comments

* FIX remove random_state in sparse.rand

* FIX spelling doc

* FIX cite example in user guide and docstring

* FIX olivier comments

* EHN improve the example comparing all the pre-processing methods

* FIX/DOC remove title

* FIX change the scaling of the figure

* FIX plotting layout

* FIX ratio w/h

* Reorder and reword the plot_all_scaling example

* Fix aspect ratio and better explanations in the plot_all_scaling.py example

* Fix broken link and remove useless sentence

* FIX fix couples of spelling

* FIX comments joel

* FIX/DOC address documentation comments

* FIX address comments joel

* FIX inline sparse and dense transform

* PEP8

* TST/DOC temporary skipping test

* FIX raise an error if n_quantiles > subsample

* FIX wording in smoothing_noise example

* EXA Denis comments

* FIX rephrasing

* FIX make smoothing_noise to be a boolearn and change doc

* FIX address comments

* FIX verbose the doc slightly more

* PEP8/DOC

* ENH: 2-ways interpolation to avoid smoothing_noise

Simplifies also the code, examples, and documentation

* add test for _preprocess_data and make it consistent

* fix pep8

* add doc, cast systematically y in X.dtype and update test_coordinate_descent.py

* test if input values don't change with copy=True

* test if input values don't change with copy=True #2

* fix doc

* fix doc #2

* fix doc #3

removing exception handling in favor of conditional check

…y calculation (scikit-learn#11464)

* Fix to allow M

* Updated MAE test to consider sample_weights in calculation

* Removed comment

* Fixed: E501 line too long (82 > 79 characters)

* syntax correction

* Added fix details

* Changed to use consistent datatypes during calculaions

* Corrected formatting

* Requested Changes

* removed explicit casts

* Removed unnecessary explicits

* Removed unnecessary explicit casts

* added additional test

* updated comments

* Requested changes incl additional unit test

* fix mistake

* formatting

* removed whitespace

* added test notes

* formatting

* Requested changes

* Trailing space fix attempt

* Trailing whitespace fix attempt #2

* Remove trailing whitespace

* Add averaging option to AMI and NMI

Leave current behavior unchanged

* Flake8 fixes

* Incorporate tests of means for AMI and NMI

* Add note about `average_method` in NMI

* Update docs from AMI, NMI changes (#1)

* Correct the NMI and AMI descriptions in docs

* Update docstrings due to averaging changes

- V-measure
- Homogeneity
- Completeness
- NMI
- AMI

* Update documentation and remove nose tests (#2)

* Update v0.20.rst

* Update test_supervised.py

* Update clustering.rst

* Fix multiple spaces after operator

* Rename all arguments

* No more arbitrary values!

* Improve handling of floating-point imprecision

* Clearly state when the change occurs

* Update AMI/NMI docs

* Update v0.20.rst

* Catch FutureWarnings in AMI and NMI

…13243)

* Remove unused code

* Squash all the PR 9040 commits

initial PR commit

seq_dataset.pyx generated from template

seq_dataset.pyx generated from template #2

rename variables

fused types consistency test for seq_dataset

a

sklearn/utils/tests/test_seq_dataset.py

new if statement

add doc

sklearn/utils/seq_dataset.pyx.tp

minor changes

minor changes

typo fix

check numeric accuracy only up 5th decimal

Address oliver's request for changing test name

add test for make_dataset and rename a variable in test_seq_dataset

* FIX tests

* TST more numerically stable test_sgd.test_tol_parameter

* Added benchmarks to compare SAGA 32b and 64b

* Fixing gael's comments

* fix

* solve some issues

* PEP8

* Address lesteve comments

* fix merging

* avoid using assert_equal

* use all_close

* use explicit ArrayDataset64 and CSRDataset64

* fix: remove unused import

* Use parametrized to cover ArrayDaset-CSRDataset-32-64 matrix

* for consistency use 32 first then 64 + add 64 suffix to variables

* it would be cool if this worked !!!

* more verbose version

* revert SGD changes as much as possible.

* Add solvers back to bench_saga

* make 64 explicit in the naming

* remove checking native python type + add comparison between 32 64

* Add whatsnew with everyone with commits

* simplify a bit the testing

* simplify the parametrize

* update whatsnew

* fix pep8

* initial commit

* used random class

* fixed failing testcases, reverted __init__.py

* fixed failing testcases #2
- passed rng as parameter to ParameterSampler class
- changed seed from 0 to 42 (as original)

* fixed failing testcases #2
- passed rng as parameter to SparseRandomProjection class

* fixed failing testcases #4
- passed rng as parameter to GaussianRandomProjection class

* fixed failing test case because of flake 8

…scikit-learn#10591)

* Initial add DET curve to classification metrics

* Add DET to exports

* Fix DET-curve doctest errors

- Sample snippet in  model_evaluation documentation was outdated.

* Clarify wording in DET-curve computation

- Align to the wording of ranking module to make it consistent.
- Add correct describtion of input and outputs.
- Update and fix non-existent links

* Beautify DET curve documentation source

- Limit line length to 80 characters.

* Expand DET curve documentation

- Add an example plot to show difference between ROC and DET curves.
- Expand Usage Note section with background information and properties
of DET curves.

* Update DET-curve documentation

- Fix typos and some grammar improvements.
- Use named references to avoid potential conflicts with other sections.
- Remove unneeded references and improved existing ones by using e.g.
using versioned links.

* Select relevant DET points using slice object

* Remove some dubiety from DET curve doc-string

* Add DET curve contributors

* Add tests for DET curves

* Streamline DET test by using parametrization

* Increase verbosity of DET curve error handling

- Explicitly sanity check input before computing a DET curve.
- Add test for perfect scores.
- Adapt indentation style to match the test module.

* Add reference for DET curves in invariance test

* Add automated invariance checks for DET curves

* Resolve merge artifacts

* Make doctest happy

* Fix whitespaces for doctest

* Revert unintended whitespace changes

* Revert unintended white space changes #2

* Fix typos and grammar

* Fix white space in doc

* Streamline test code

* Remove rebase artifacts

* Fix PR link in doc

* Fix test_ranking

* Fix rebase errors

* Fix import

* Bring back newlines

- Swallowed by copy/paste

* Remove uncited ref link

* Remove matplotlib deprecation warning

* Bring back hidden reference

* Add motivation to DET example

* Fix lint

* Add citation

* Use modern matplotlib API

Co-authored-by: Jeremy Karnowski <jeremy.karnowski@gmail.com>
Co-authored-by: Julien Cornebise <julien@cornebise.com>
Co-authored-by: Daniel Mohns <daniel.mohns@zenguard.org>

Better CSS for doc links