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
6c033bd585
fix: resize oob improvements, train score when early stopping
2014-01-04 17:57:04 +01:00
181c515993
moved fit_more to warm_start=True
2014-01-04 16:25:16 +01:00
f512bd82c9
renamed partial_fit -> fit_more for GBRT
2014-01-04 14:07:42 +01:00
97392248b2
Merge branch 'master' into gbrt-enh-stackrec-greedy
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Conflicts:
sklearn/ensemble/tests/test_gradient_boosting.py
2013-12-09 14:58:10 +01:00
1b8ea52741
max_leaf_nodes has precedence over max_depth if the former is not None.
2013-12-02 20:13:57 +01:00
d2f3a8a3da
ENH: refactor warnings 1
2013-11-29 13:55:38 +01:00
ab14a08c76
remove check for condition that might not hold
2013-11-21 17:46:40 +01:00
e62d196fe7
Merge branch 'master' into gbrt-enh-stackrec-greedy
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Conflicts:
sklearn/ensemble/_gradient_boosting.c
sklearn/tree/_tree.c
sklearn/tree/_tree.pxd
sklearn/tree/_tree.pyx
sklearn/tree/tree.py
2013-11-08 14:35:33 +02:00
c5ce49be92
fix: Huber loss function in gradient_boosting fails if negative_gradient is not called before __call__; now computes on-demand.
2013-11-07 17:33:25 +02:00
edb4a2d249
support 'zero' init, more tests for ZeroEstimator
2013-11-05 10:01:31 +02:00
bef7d4007f
use assert_equal if possible
2013-11-03 15:44:10 +02:00
e9cea77bd8
PriorityQueue for best-first tree growing
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max_leaf_nodes instead of complete parameter
2013-11-03 09:40:24 +02:00
3914a229da
fix: use regressor in regression test
2013-11-02 11:53:32 +02:00
d7e5802037
add tests for complete
2013-11-02 11:36:19 +02:00
ecd606bfb4
added monitor callback w/ early stopping support
2013-11-01 21:25:30 +02:00
098f630d70
GBRT enhancements:
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Moved verbose output code to VerboseReporter class.
Cosmit: logical structured code blocks
Refactored: moved init state to method
Added partial_fit to GradientBoosting
Fix: is_classification not available; n_features not n_features_
Tests
Add ``partial_fit`` to docs
2013-11-01 21:23:02 +02:00
fd3a816afb
renamed supported_loss to _SUPPORTED_LOSS (constants)
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add test for deprecated warning
2013-08-24 19:04:11 +03:00
b952cdb052
GBRT checks if ``loss`` is in self.supported_loss
2013-08-24 18:08:04 +03:00
Andreas Mueller