* Return correct ridge parameter alpha_ and lambda_ for regression
* Add test for coefficients and fix style
* Move sklearn.utils.testing to a more reasonable position.
* Make flake8 happy
* Code cleanup and entry in whats_new.rst
* doc: state that parameter C can receive an array
* add more details in doc, and check the dim of C
* doc: state that parameter C can receive an array
* add more details in doc, and check the dim of C
* a little modification
* minor modifications and make line length less than 79 characters
* remove the backslash and correct typos
* meet PEP8's E128 requirement
* use .format and add a test
* ENH Accept keyword parameters to hyperparameter search fit methods
Deprecate ``fit_params`` as a constructor argument to the hyperparameter search classes and instead accept keyword parameters to the ``fit`` methods. This makes the ``fit`` methods of these functions conform to the Estimator API and allows the use of hyperparameter search functions in other CV utility functions such as ``cross_val_predict``.
* CR: Expanded tests, remove deprecated use in Ridge
* Make tests consistent in Python 2 and 3
* Convert ElasticNet Multioutput to floating.
* Remove all the float64 coordinate_descent.
* Add the necessary cblas for use fused types.
* Fix zeros dtype issue in cd_fast.
* Remove cblas files.
* Change random seed to let test_lle_simple_grid pass.
* Add tests to check floatting issue for MultiTaskElasticNet.
* Update cblas_sscal.c
* 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
* 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
* Remove Python 2.6 support
Some details about some slightly orthogonal changes:
* Note about cheking safely for nan is likely not valid any more (commit
introducing it is c80ca91b)
* scipy.linalg.qr econ parameter removed since scipy 0.9 in favour of
mode='economic'
* Remove unnecessary libgfortran in conda create command
* Putative fix by setting the random seed
* Revert unintended change
* Reinstate previous logic for checking for NaNs
* Reinstate change in error message
Error messages from Python 2.7 assertRegexp does not contain the
function name, in contrast with Python 3 assertRegex
* Fix bug 7778
* Add test_lasso_lars_vs_R_implementation
* Add a space to match the indentation
* Solve E501 line too long (80 > 79 characters)
* assert_array_almost_equal up to 12 decimals
* Tiny modification for increasing performance
* Update what's new page
* Trying to solve conflicts
* Solve conflict in doc/whats_new.rst
* use less nose.tools import to simplify future transition to activly developing test suites/runners
* assert_equal -> assert_array_equal in test_feature_hasher_pairs_with_string_values
and one missed ImportError that should be replaced with AttributeError
* test for py2.6 compat with except AttributeError
* fix importing of SkipTest
* force using nose in python2.6 for now
* there was no assert_dict_equal in py2.6. but we can use assert_equal
although failed test will look a little bit ugly
* remove nose imports from doc/datasets
ElasticNet and Lasso no longer implicitly convert float32 dtype input to float64 internally.
* Make helper functions in cd use fused types
* Import cblas float functions
* Make enet_coordinate_descent support fused types
* Make dense case work
* Refactor format
* Remove redundant change
* Add cblas files
* Avoid redundant code
* Remove redundant c files and import
* Recover unnecessary change
* Update comment
* Make coef_ type consistent
* Test float32 input
* Add user warning when fitting float32 data with small alpha
* Fix bug
* Change variable to floating type
* Make cd sparse support fused types
* Make CD support fused types when data is sparse
* Add referenced src files
* Avoid duplicated code
* Avoid type casting
* Fix indentation in test
* Avoid type casting in sparse implementation
* Fix indentation
* Fix duplicated intialization code
* Follow PEP8
* Raise tmp precision to double
* Add 64 bit computer check
* Fix test
* Add constraint
* PEP 8
* Make saxpy have the same structure as daxpy
Hopefully this fixes the problems outlined in PR #6913
* Remove wrong hardware test
* Remove dsdot
* Remove redundant asarray
* Add test for fit_intercept
* Make _preprocess_data support other dtypes
* Add concrete value
* Workaround
* Fix error msg
* Move declarartion
* Remove redundant comment
* Add tests
* Test normalize
* Delete warning
* Fix comment
* Add error msg
* Add error msg
* Add what's new
* Fix error msg
* Remove cdivision=True Cython compiler directive causing incorrect int division.
* Decrease tol for LogisticRegression fit test, perhaps needed due to test not controlling `random_state`.
* MNT Removing more deprecated stuff for v0.18
* MNT+TST Remove support for loss='l2'
* MNT Remove support for precompute='auto' for ElasticNet
* FIX/TST precompute=auto should raise a generic message
Add gradient calculation in _huber_loss_and_gradient
Add tests to check the correctness of the loss and gradient
Fix for old scipy
Add parameter sigma for robust linear regression
Add gradient formula to robust _huber_loss_and_gradient
Add fit_intercept option and fix tests
Add docs to HuberRegressor and the helper functions
Add example demonstrating ridge_regression vs huber_regression
Add sample_weight implementation
Add scaling invariant huber test
Remove exp and add bounds to fmin_l_bfgs_b
Add sparse data support
Add more tests and refactoring of code
Add narrative docs
review huber regressor
Minor additions to docs and tests
Minor fixes that deals with dealing with NaN values in targets
and old verions of SciPy and NumPy
Add HuberRegressor to robust estimator
Refactored computation of gradient and make docs render properly
Temp
Remove float64 dtype conversion
trivial optimizations and add a note about R
Remove sample_weights special_casing
address @amueller comments
Naoya Kanai