966e10c252
COSMIT PEP8
2012-12-22 16:48:17 +01:00
754c2d9533
COSMIT pep8
2012-12-22 16:48:17 +01:00
270bc8e278
TST some more tests for SGDClassifier input validation
2012-12-15 22:10:48 +01:00
8eda5e1c0e
TST document and test verbosity parameter of lars_path
2012-12-15 21:18:10 +01:00
08dff76e2c
ENH input validation only in ``fit`` in LassoLarsIC, check that error is raised.
2012-12-15 21:17:51 +01:00
116b54a8c8
Fix bug in sqnorm (used by PassiveAggressive).
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The function was using the wrong data indices T_T.
2012-11-24 23:05:52 +09:00
23ac37a4fb
API : move isotonic regression out of linear_model
2012-11-14 22:01:53 +01:00
c97e281401
FIX #1354 : machine precision assertion failure in test_liblinear_random_state
2012-11-10 20:54:07 +01:00
c9cd2b7292
FIX: lars drop for good platform specific test failure
2012-11-10 20:41:21 +01:00
7cec21bbee
TEST: decrease precision in test_lars_drop_for_good
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If the test is wrong, this will be well off. Small errors just reflect
numerical errors
2012-11-10 19:43:17 +01:00
92138a4258
COSMIT pep8
2012-11-10 14:02:29 +00:00
9e52350533
BUG: compat with numpy 1.3
2012-11-08 11:02:54 +01:00
25707c2c54
BUG: missing import introduced by rebase
2012-11-08 10:40:10 +01:00
de4fd325af
COSMIT: better comments
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Specifying exactly why a test is around is important
2012-11-08 10:39:22 +01:00
1f3f49755a
TST: difficult test for early stopping
2012-11-08 10:39:22 +01:00
428439f7ca
MISC: comment
2012-11-08 10:39:22 +01:00
2d9435c366
TST: add a test for lasso and lars
2012-11-08 10:39:22 +01:00
e290951871
ENH: early stopping for lars
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When the noise in the updates of the Cholesky becomes greater than the
max residual, it is impossible to go on in the path: giving up.
2012-11-08 10:39:22 +01:00
f739070d5f
WIP: drop for good correlated regressors
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Attempt to drop for good correlated regressors. In Lars. Doesn't seem to
be working, as it is give a significantly different result than the
lasso (failing test)
2012-11-08 10:39:22 +01:00
a911ad10fb
MISC: address comments
2012-11-08 10:32:58 +01:00
156566e6a9
ENH: early stopping LARS for degenerate active set
2012-11-08 10:31:13 +01:00
e18465da6a
ENH: multi-target Lars: lists rather than arrays
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Because the path length varies, arrays lead to wasted memory and trailing
zeros (or ones, depending on the implementation).
2012-11-08 10:24:56 +01:00
48dd2ac338
TEST: test that alpha is decreasing in LassoLars
2012-11-08 10:24:56 +01:00
e115469160
TEST: one addition test on the length of the path
2012-11-08 10:24:56 +01:00
4f41de9f35
BUG: LassoLars path ending contained junk
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Addresses mailing list discussion
http://sourceforge.net/mailarchive/forum.php?thread_name=20120918124544.GF27767%40phare.normalesup.org&forum_name=scikit-learn-general
2012-11-08 10:24:56 +01:00
34037306ab
Remove transform from PassiveAggressive*.
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It really only makes sense if the estimator supports L1-penalty.
2012-11-08 15:21:19 +09:00
a3670c0fb4
Remove predict_proba from Perceptron and PassiveAggressiveClassifier.
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Fixes #1336 .
2012-11-07 14:18:34 +09:00
27be154754
Add tests for partial fit.
2012-11-06 01:07:44 +09:00
da98830f7a
Add one more test for PassiveAggressiveRegressor.
2012-11-05 22:26:42 +09:00
0dcb61fc39
Test PA-II (regression).
2012-11-05 21:17:04 +09:00
97f594a935
Add squared epsilon insensitive loss.
2012-11-05 21:15:51 +09:00
89e06ada23
Test different losses.
2012-11-05 20:46:14 +09:00
8b73f406b9
Implement and test PA-II.
2012-11-05 20:13:20 +09:00
65b035ff78
Fix many bugs and test PA-I.
2012-11-05 18:01:35 +09:00
00c380b82a
Cosmit: random_state is not necessary.
2012-11-05 16:56:44 +09:00
25284b9cf1
Merge branch 'sgd_learners' of https://github.com/zaxtax/scikit-learn into passive_aggressive
2012-11-05 16:24:42 +09:00
f67e0d2f1e
Fixed docstrings and seed tests
2012-11-02 09:52:05 -07:00
3c854a2fef
COSMIT pep8
2012-10-31 15:36:03 +00:00
f65efcf8eb
More use sklearn.utils.testing.
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My model is training :)
2012-10-25 21:21:22 +09:00
6610659947
Added tests
2012-10-21 07:59:37 -07:00
e64cea0342
ENH add random seed to logistic regression
2012-10-18 13:48:10 +02:00
60ae168464
COSMIT rm unused import
2012-10-16 14:36:49 +02:00
a06c367ba2
ENH sparse matrix support in randomized logistic regression
2012-10-16 14:34:48 +02:00
8d3c75feff
Store X as an ordered array.
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This simplifies and makes more efficient the `fit` and transform
method (re-ordering in transform is no longer needed).
2012-10-16 14:18:43 +02:00
04251e155d
Better tests + cosmetic changes.
2012-10-16 14:18:43 +02:00
342c5be9f1
ENH: Consider order in X for IsotonicRegression.
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Before, IsotonicRegression assumed X was an increasing sequence. This
allows to shuffle both X, y (see the test) and obtain the same
result. This makes IsotonicRegression behave more like a standard
Regression (which is what I would expect).
2012-10-16 14:18:43 +02:00
72e71bb439
ENH address @agramfort's comments, fix some doctests
2012-10-11 20:56:03 +01:00
b39609af4e
ENH rename rho in SGD
2012-10-11 20:56:03 +01:00
16aabc7c3f
ENH rename rho to l1_ratio in ElasticNet and friends
2012-10-11 20:56:03 +01:00
244e8a68fa
Merge pull request #1187 from ogrisel/bugfix-logistic-ovr-probabilities
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MRG: FIX: wrong probabilities for OvR LogisticRegression
2012-09-30 06:09:51 -07:00
Andreas Mueller