0485ada58b
General spelling fixes
2015-12-16 09:46:42 -08:00
776e53b127
skip unstable tests on 32bit platform
2015-11-02 15:21:22 -05:00
fea218e5cf
In tree, min_samples_split and min_samples_leaf now accept float number as percentage.
2015-10-24 23:18:52 +02:00
e3afc0e8c9
MAINT move custom error/warning classes into sklearn.exceptions
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ENH NonBLASDotWarning -> EfficiencyWarning; Improve error message
DOC Add exceptions module to modules/classes.rst
MAINT Move ConvergenceWarning, UndefinedMetricWarning et al into exceptions
MAINT Remove ChangedBehaviorWarning from base
DOC/FIX Improve DataConversionWarning's docstring
2015-10-19 22:35:35 +02:00
5a0db1717a
1. Added parameter prefit to pass in a fitted estimator.
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2. Use assert_warns instead of catch_warnings
3. Remove depracation warnings in common tests.
2015-10-09 01:57:36 -04:00
2416e2aee6
Catch filters instead of removing the tests
2015-10-05 11:24:02 -04:00
02c0029baa
ENH gbt sparse support
2015-09-28 13:44:12 -07:00
470b9a48be
Merge pull request #5228 from jmschrei/gb_apply
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[MRG+1] Apply method added to GradientBoosting
2015-09-10 10:37:25 +02:00
bc225a5e1a
ENH apply method added to Gradient Boosting
2015-09-10 10:32:51 +02:00
2f099334f9
MAINT deprecate 1d input arrays for all estimators
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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
2015-09-09 15:49:58 +02:00
8453daa6b9
Use expit function to compute the probability in ExponentialLoss class.
2015-06-08 13:03:52 -04:00
a8626b36a6
TST/COSMIT remove nose call boilerplate
2015-05-28 14:54:01 -04:00
d89c215013
Add tags to classifiers and regressors to identify them as such.
2015-03-31 19:59:49 -04:00
93008482bd
DOC/TST docstring --> comment
2015-03-26 18:41:19 +05:30
d0db91a144
add huber to non-uniform sample weight toy test case
2015-03-26 11:44:53 +01:00
5ba271bd39
cosmit
2015-03-25 14:23:07 +01:00
5018a44ccf
add regression test case for issue 4447
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- fix another test
2015-03-25 14:22:31 +01:00
cd2ee7e454
MAINT docstring --> comments to prevent nose from using doc in verbose mode
2015-03-21 11:16:49 +05:30
0036dd0319
ENH make defensive copies in GradientBoosting*.staged_decision function.
2015-02-24 16:28:33 -05:00
92ed5eee42
FIX ensure that negative float max_features will lead to an error
2015-02-03 13:39:18 +01:00
92b90815a6
FIX Ensure at least 1 feature is sampled when max_features is a float
2015-02-03 13:30:17 +01:00
0bca2ffdfa
FIX Refactor _is_fitted method into check_is_fitted.
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DOC Make the docstring of NotFittedError class to conform to pep8.
DOC Make the error message of check_is_fitted more newbie friendly.
2015-01-12 00:33:40 +05:30
129e319f99
FIX the try except block to recognize NotFittedError
2015-01-12 00:33:40 +05:30
6b548f96f1
MAINT remove deprecated loss in gradient boosting
2014-10-24 12:58:13 +02:00
d4405cbf6c
MAINT remove deprecated oob_score_
2014-10-21 17:33:48 +02:00
cd7b43ccf9
TST make catch_warnings blocks more robust
2014-10-12 18:20:18 +02:00
85b2c783ce
add probability output for exponential loss
2014-09-22 00:29:38 +02:00
e6fa80014b
non-uniform weight test case for both reg and clf and all losses
2014-09-22 00:12:38 +02:00
05fbc6423d
fix: sample_weight is None in Huber.deviance
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fix: sample_weight multiplication in Huber leaf updates
more tests (non-uniform weights, weight consistency and invariance to scaling, deviance consistence)
2014-09-18 10:42:36 +02:00
d9925961df
fix: add **kwargs to Multinomial loss' negative_gradient
2014-09-17 12:14:26 +02:00
93b2b7dae1
fix: consider sample_weights in robost init estimator and negative_gradient
2014-09-17 12:14:26 +02:00
fd952cc0ec
sample weight support for robust regression via weighted percentile algo
2014-09-17 12:14:26 +02:00
297b36a9b1
update tests for new exception types
2014-09-17 12:14:26 +02:00
6fe6c34c15
adressed Olivier's feedback
2014-09-17 12:14:26 +02:00
2503d35039
cosmit: doc
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raise ValueError for sample_weights and robust regression
2014-09-17 12:14:26 +02:00
f98388e31f
more tests
2014-09-17 12:14:26 +02:00
7f4c974d6b
Sample weights for gradient boosting
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Exponential loss for classification + predict_proba refactoring
2014-09-17 12:14:26 +02:00
ffd13c389b
fix: i might be undefined
2014-07-31 23:47:51 +02:00
9131413aaa
Added warm start to random forests.
2014-07-25 13:58:06 +02:00
c9789c7edf
COSMIT clean up tests with pyflakes
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test_ridge.py contained two duplicate functions.
2014-07-22 16:10:16 +02:00
72c60eba94
gbrt: min_weight_fraction_leaf value test
2014-07-02 11:47:31 +02:00
c7db70ac9f
removed unused variables and imports, add used imports where missing.
2014-06-08 21:44:01 +02:00
b0e11f575e
Added extra check to feature importances
2014-03-19 10:38:16 +05:30
ffb89eb3a2
Added _LearntSelectorMixin in BaseGradientBoosting
2014-03-13 23:46:23 +05:30
dbc26ce996
COSMIT remove unused imports and variables
2014-02-03 19:43:56 +11:00
9d7e30c65a
COSMIT: PEP8 in test_gradient_boosting.py
2014-01-16 14:08:50 +01:00
8b9b1ee78c
fix: remove print from gbrt test
2014-01-08 16:15:40 +01:00
a8bdbff5f9
do not alter n_estimators after early stopping
2014-01-06 16:26:08 +01:00
e0c635f11b
cosmit
2014-01-06 11:07:46 +01:00
f9104f64d1
warm_start semantics now fit exactly n_estimators rather than self.estimators_ + self.n_estimators
2014-01-05 11:57:38 +01:00
seales