4744e062ff
TST fix binomial deviance ( #18250 )
2020-08-31 13:29:11 +02:00
989613e5c3
DEP Deprecate n_classes_ in GradientBoostingRegressor ( #17702 )
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Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
2020-08-13 19:25:55 +02:00
068c4e6e00
FIX fix multinomial deviance by taking the weighted average instead of the sum ( #17694 )
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Co-authored-by: Markus Rempfler <markus.rempfler@tum.de>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
2020-06-26 18:57:36 +02:00
f93f560bb9
ENH add support for sample weights in MAE ( #17225 )
2020-05-27 15:03:43 +02:00
19c068a2ec
MNT towards removing assert_equal, etc ( #14222 )
2019-07-01 09:13:32 -04:00
a5743ed36f
TST add test for LAD-loss and quantile loss equivalence (old GBDT code) ( #14086 )
2019-06-13 14:52:56 -04:00
ea63c56638
FIX several bugs in initial predictions for GBDT ( #12983 )
2019-03-01 07:00:41 +01:00
b6854944fb
[MRG+1] Corrected sign error in QuantileLossFunction ( #6429 )
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* Corrected sign error in QuantileLossFunction
2016-12-22 18:09:58 +01:00
9b2aac9e5c
[MRG + 1] [TST] (half-cosmetic) use less nose.tools import to simplify future transition to py.test ( #7384 )
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* 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
2016-10-07 12:46:52 -04:00
a87011262a
FIX precision to float64 across the codebase
2015-10-16 11:20:29 +02:00
cd2ee7e454
MAINT docstring --> comments to prevent nose from using doc in verbose mode
2015-03-21 11:16:49 +05:30
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
75f6e015c9
more tests for weighted percentile
2014-09-17 12:14:26 +02:00
6fe6c34c15
adressed Olivier's feedback
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
2ffb484adb
COSMIT pep8
2013-05-04 10:43:39 +02:00
44360a31f3
pep8 and assert_equal instead of assert
2013-01-26 18:19:13 +01:00
1a09e204a1
add loss function for gradient boosting binomial deviance
2013-01-26 17:26:05 +01:00
Christian Lorentzen