69ea066412
ENH Minimal Generalized linear models implementation (L2 + lbfgs) ( #14300 )
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Co-authored-by: Christian Lorentzen <lorentzen.ch@googlemail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
2020-03-04 14:08:24 +01:00
5573abbb99
MNT Removed deprecated logistic_regression_path ( #15791 )
2019-12-04 12:24:10 -05:00
0a7adef005
MNT Make modules private in linear_model ( #15324 )
2019-10-23 15:34:26 +02:00
6a8b3d4c4b
DOC reorganize API Ref of linear models ( #15115 )
2019-10-08 16:57:43 +02:00
fec7670ad0
ENH Enable the "sufficient stats" mode of LARS ( #11699 )
2019-03-06 08:06:47 +01:00
0f94f2962b
MNT simple deprecations and removals for 0.21 ( #12238 )
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Part of #11992 .
These were all the things that seemed pretty straight-forward. It's actually a bit bulky but should still be easy to review, hopefully.
2018-10-11 14:56:37 -04:00
dc43486806
Remove unused imports ( #9235 )
2017-07-01 05:57:54 -07:00
c10c88622a
Deprecate randomized_l1 ( #9031 )
2017-06-30 18:20:25 +02:00
7e79adca9d
Huber regressor
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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
2016-02-25 16:31:08 -05:00
94eb61960a
ENH add sag solver in LogisticRegression and Ridge
2015-09-10 13:28:02 -04:00
4ceffe05a1
Adding Implementation of SAG
2015-09-10 13:27:04 -04:00
ef17f8067b
ENH: Improvements in the Theil-Sen regressor
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- Renamed TheilSen to TheilSenRegressor
- Renamed n_iter parameter to max_iter
- Better warning message when maximum iteration number reached
- Added docstring for fit
- Removed backend and max_nbytes parameters in Parallel
- Removed n_dim return value from _check_subparams
- Some PEP8 corrections
- Added an attribute n_iter_ to show number of iterations
- Removed unnecessary array to list conversion ix = list(ix)
- Remove random_state_ as attribute
2014-09-24 22:58:29 +02:00
8dbec4f76c
Merge branch 'master' into theilsen
2014-09-06 10:14:12 +02:00
4cd177758f
ENH: Merge MultinomialLR into LR with multi_class='multinomial'
2014-08-21 17:37:37 +02:00
13ca2b2859
ENH multinomial logistic regression using L-BFGS
2014-08-21 17:37:37 +02:00
6e4f02c427
Implementation of logistic_regression_path.
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This is mostly the code from Gael's logistic_cv branch. My work is only some
minor cleanup some added tests and benchmarking.
2014-07-22 16:57:39 +02:00
d3cddfeab0
API: naming: CamelCase class -> camel_case function
2014-07-19 13:11:14 +02:00
601b82b596
Merge branch 'master' into theilsen
2014-03-02 22:39:06 +01:00
a917a02083
ENH: MultiTaskElasticNet (and Lasso) CV
2014-01-21 08:41:02 +11:00
d4519d2c80
Added multiple linear Theil-Sen regression
2014-01-14 21:57:10 +01:00
c2a2bfe45b
Rename RANSAC to RANSACRegressor
2013-10-20 15:58:04 +02:00
0cd1374f14
Add RANSAC to __init__ of linear_model sub-package
2013-10-20 15:57:56 +02:00
372ca22492
ENH OrthogonalMatchingPursuitCV estimator
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FIX: work with max_iter=1, though it does not make sense
DOC add OrthogonalMatchingPursuitCV docstrings
2013-07-26 09:50:53 +02:00
8861833ec9
DOC spellfixes
2013-06-29 16:18:23 +03:00
754c2d9533
COSMIT pep8
2012-12-22 16:48:17 +01:00
23ac37a4fb
API : move isotonic regression out of linear_model
2012-11-14 22:01:53 +01:00
65b035ff78
Fix many bugs and test PA-I.
2012-11-05 18:01:35 +09:00
5590ce59ce
Adding PassiveAggressiveRegressor estimator
2012-10-24 08:07:28 -07:00
8f22486d1b
Split out PassiveAggressive Classifier into its own object
2012-10-24 07:55:51 -07:00
04251e155d
Better tests + cosmetic changes.
2012-10-16 14:18:43 +02:00
77e69edcec
COSMIT rm deprecated stuff -- lots of it
2012-09-20 21:40:33 +02:00
c2aabf09bd
BUG rm LARS from linear_model.__init__
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from sklearn.linear_model import * raised an exception.
2012-09-17 20:40:44 +02:00
f28d0887fe
ENH: Isotonic regression
2012-09-15 16:40:42 +02:00
006e7ef801
Add __all__ for the second half of the scikit
2012-09-04 18:00:49 +01:00
02a831a010
Remove LARS and LassoLARS
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These classes were renamed and deprecated in version 0.9.
2012-09-01 20:02:13 +02:00
21706e36b9
ENH + DOC : add MultiTaskElasticNet + doc + 1 example
2012-08-07 15:51:12 +02:00
dcbf5a61d2
ENH : MultiTaskLasso works (still draft)
2012-08-07 15:51:12 +02:00
a882bedcc3
MISC: address @ogrisel and @mblondel's comments
2012-01-31 18:11:05 +01:00
19331b5ae3
DOC : adding doc for Randomized sparse linear models + fix test
2012-01-31 18:07:06 +01:00
ab4c418a48
mv randomized_lasso.py randomized_l1.py
2012-01-31 18:06:14 +01:00
e4919e61bd
Add a randomized logistic
2012-01-31 18:05:53 +01:00
b0c119ca52
ENH: Add randomized lasso
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Feature selection using Lasso (Meinshausen and Bulmhan 2008)
2012-01-31 18:01:02 +01:00
5e3ea55706
Add Perceptron.
2012-01-29 02:34:12 +09:00
0d48f49bbf
Merge dense and sparse SGD implementations.
2012-01-14 03:21:40 +09:00
25c93f4af6
COSMIT: pep8
2011-12-15 17:24:53 +01:00
c40dbf739f
DOC: Standardize the module documentation format (work in progress)
2011-11-30 10:30:13 +01:00
ff3f814a1b
COSMIT pep8 whitespace
2011-11-20 21:16:52 +01:00
ddf4b72109
Move project directory from scikits.learn to sklearn
2011-09-02 12:06:57 +02:00
68f27e3790
Revert "Move project directory from scikits.learn to sklearn"
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This reverts commit fd0d3b879d
2011-09-02 12:03:18 +02:00
fd0d3b879d
Move project directory from scikits.learn to sklearn
2011-09-02 11:38:24 +02:00
Roman Yurchak