8f2780f579
Make BaggingClassifier use if_delegate_has_method in decision_function
2015-02-26 10:53:37 +01:00
feceab6f62
FIX test for consistent handling on empty input data
2015-02-26 10:45:06 +01:00
3468e00471
Merge pull request #4057 from amueller/dtype_object_conversion
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[MRG + 2] make check_array convert object to float.
2015-02-24 22:33:20 +01:00
0036dd0319
ENH make defensive copies in GradientBoosting*.staged_decision function.
2015-02-24 16:28:33 -05:00
44d81a0ec3
FIX: add except* in Splitter.init definitions
2015-02-23 08:19:10 +01:00
96d4b3e709
more robust check for dtype object
2015-02-18 14:11:58 -08:00
cd5166e82f
make check_array convert object to float.
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fix dtype check, add test. unfriend all multi-output estimators on facebook.
try to fix what is happening to y (by doing nothing to y)
make test work...
Make everything accept object y or say "invalid label"
fix multioutput linear models
add test for sensible error message.
2015-02-15 12:13:41 -05:00
420daac269
Merge pull request #4190 from trevorstephens/refactor_cw
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MRG+2: Refactor - Farm out class_weight calcs to .utils
2015-02-06 08:24:27 +01:00
38104ff4e8
Merge pull request #4193 from lesteve/deactivate-travis-default-venv
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CI: test with NumPy 1.6.1, fix for its broken bincount
2015-02-03 16:25:36 +01:00
cfd68ef435
Merge pull request #4198 from arjoly/gbrt-fix-percent-max_features
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FIX Ensure at least 1 feature is sampled when max_features is a float
2015-02-03 15:59:56 +01:00
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
67dcd99d82
TST fix tests with numpy 1.6.1
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np.bincount raises an Exception with empty input arrays for numpy versions < 1.6.2
Add utils.fixes.bincount to tackle this issue and use it instead of np.bincount
2015-02-01 15:49:49 +01:00
f75c98b872
refactor forests & trees class_weight calc
2015-01-31 18:27:29 -08:00
b35b2fdad3
Add predict_log_proba method to GradientBoostingClassifier
2015-01-29 20:09:48 +01:00
247ad47361
Merge pull request #4153 from hsalamin/remove_exp_warning
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FIX get rid of overflow warning in gradient boosting
2015-01-23 17:33:31 +01:00
9ca04c24fe
Fix for overflow warning
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Use expit function to compute the negative gradient and
avoid exp overflow.
2015-01-23 11:43:54 +01:00
f6c7252ded
DOC staged_* returns generators. Fixes #3831 .
2015-01-22 17:34:41 -05:00
6ffc68556f
FIX Support for negative values of n_jobs
2015-01-21 12:58:31 +01:00
a413f875f1
DOC minor fixes do docstrings, don't document deprecated parameters.
2015-01-16 11:55:02 -05:00
b3fbccca38
FIX various mismatch between docstring and signature params
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DOC max_iterations -> max_iter. Make it consistent with kmeans
MAINT Replace the deprecated dx parameter with d in the docstrings
MAINT Deprecation warning for max_iterations parameter.
2015-01-16 11:54:57 -05:00
c970fb51e7
COSMIT spelling
2015-01-15 15:09:35 -05:00
b7d9c3e0aa
FIX: ensure that feature importances are properly scaled
2015-01-13 16:08:58 +01:00
35c2535bfc
rename cw option to subsample & refactor its implementation
2015-01-12 21:27:13 -08:00
b541191754
Merge branch 'master' into rf-class_weight
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Conflicts:
doc/whats_new.rst
sklearn/ensemble/forest.py
sklearn/tree/tree.py
2015-01-12 19:15:21 -08:00
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
abd31d2cad
MAINT Make uniform the error raised for not fitted condition
2015-01-12 00:33:40 +05:30
cad87b578c
rename vars & copy sample_weight
2015-01-10 11:49:42 -08:00
9c7566e5df
Merge branch 'master' into rf-class_weight
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Conflicts:
doc/whats_new.rst
2015-01-08 07:56:19 -08:00
ac9ab961bb
Y-org rename & whats_new update
2015-01-08 02:31:24 -08:00
2b24ccefa0
parameter validation checks & tests for errors
2015-01-03 13:15:42 -08:00
e77aac8e58
Documentation of max depth parameter
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Changed the docstring
Few docstring changes
2014-12-29 20:04:25 +05:30
085d677ea2
add class_weight to trees, expand tests & minor refactor
2014-12-22 16:50:58 -08:00
5b90e97ebf
TST remove SVR(probability=True) from AdaBoost tests
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Doesn't seem to have been testing anything, because CustomSVR doesn't
have predict_proba.
2014-12-17 10:37:33 +01:00
4c77ae897b
expanded class_weight dimension fix
2014-12-14 15:08:13 -08:00
b131ad23fa
add multioutput support & bootstrap auto mode
2014-12-14 13:31:31 -08:00
de35beab43
add support for class_weights
2014-12-11 16:22:26 -08:00
89857698a9
DOC clarify RandomTreesEmbedding docstring
2014-12-08 20:30:00 +01:00
7c50e6c8eb
various docstring fixes for web docs
2014-11-30 17:59:42 -08:00
c24ada07a2
ENH use threading backend for features importance parallelisation
2014-11-28 18:55:46 +01:00
373e641c52
MAINT refactor gradient boosting code
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Fixes gh-3790
2014-11-25 17:23:00 +01:00
8621f00f6f
Merge pull request #3173 from arjoly/sparse-tree
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[MRG] Sparse input support for decision tree and forest
2014-11-21 10:10:33 +01:00
ee53f51f15
TST stronger non-regression test for #3815
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Also fixed the testing imports.
2014-11-17 23:00:33 +01:00
248a5037f6
Fixed issue 3815. Discrete AdaBoostClassifier now fails early if the base classifier if worse than random.
2014-11-07 13:42:19 +00:00
8b3b0710c3
FIX duplicate type coercision + DOC fix inversion between csc and csr
2014-11-06 13:58:34 +01:00
c6af5c6e94
ENH adaboost should accept c and fortran array
2014-11-06 13:58:31 +01:00
c03c01a504
ENH Bring sparse input support to tree-based methods
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Author: Arnaud Joly <arnaud.v.joly@gmail.com>
Fares Hedayati <fares.hedayati@gmail.com>
2014-11-06 13:58:28 +01:00
e6835a7aac
Merge pull request #3779 from arjoly/sw-dummy-regressor
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[MRG+1] Add sample_weight support to Dummy Regressor
2014-11-04 09:50:01 +01:00
6b548f96f1
MAINT remove deprecated loss in gradient boosting
2014-10-24 12:58:13 +02:00
Andreas Mueller