5a58e56826
Merge pull request #5487 from arjoly/example-node
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[MRG+1] Add an example and a method to analyse the decision tree stucture
2015-10-22 13:31:49 +02:00
744d161d37
Merge pull request #5431 from hlin117/nan-targets
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[MRG + 2] Add check to regression models to raise error when targets are NaN
2015-10-22 09:36:12 +02:00
7d4755e317
Add a decision_path function to forest estimator
2015-10-21 17:05:56 +02:00
62633f701b
Addressed comments on PR #5451
2015-10-21 10:24:23 +02:00
5db2adf93c
MAINT Removed deprecated stuff.
2015-10-21 10:24:23 +02:00
34c8399be1
#5322 : Fixing the fix - now RFs should be okay
2015-10-20 10:36:47 -05:00
d62e316882
#5322 : Resolving Random Forest build errors (bad input shape)
2015-10-20 10:36:47 -05:00
b4e746bb5c
Resolving rebase conflicts on forest.py
2015-10-20 10:33:22 -05:00
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
85223b9bcc
a common test to check if classifiers fail when fed regression targets
2015-10-14 14:46:13 -04:00
4243412173
fixes bug in oob_score when X is sparse.csc matrix [refs #4744 ]
2015-07-17 14:46:14 +05:30
d92d35f8fe
Merge pull request #4783 from tokoroten/decrease_randomforest_memory
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[MRG+1] RandomForest decrease allocated memory when using bootstrap option. (Fix issue#4774)
2015-07-11 12:52:09 -05:00
4ab89c5a84
upd randomforest docstring
2015-07-06 23:52:43 -04:00
9f06156f20
add a new int array to store indices
2015-06-24 11:22:01 -04:00
0650d5502e
DOC adding backlinks to docstrings
2015-06-03 00:24:04 -04:00
02fedc6ca3
autopep8 E501
2015-06-02 21:12:30 +09:00
4515cecffb
change valiable name to meaningful.
2015-06-02 21:06:20 +09:00
123a8c99b6
FIX add class_weight="balanced_subsample" to the forests to keep backward compatibility to 0.16
2015-06-01 12:49:53 -04:00
eedc1cddab
Use more natural class_weight="auto" heuristic
2015-06-01 12:49:53 -04:00
bcd7e9b19c
refactoring to DRY.
2015-05-29 19:45:08 +09:00
cc84db3775
refactoring to simplify
2015-05-28 16:12:48 +09:00
21dbe72345
randomforest decrease allocated memory
2015-05-28 15:43:02 +09:00
64e553398b
DOC document missing attributes
2015-05-12 15:00:38 +02:00
027eb6d3a1
ForestClassifier.predict docstring correction
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See http://stats.stackexchange.com/q/127077/9964 for some discussion....
2015-04-27 23:03:48 -04:00
32290ad503
FIX use the new notfittederror in feature_importances_
2015-04-20 17:27:58 +02:00
294a6219e2
FIX properly raised not fitted error
2015-04-20 17:27:58 +02:00
4b8b20015d
ENH Factor out validation of X for apply/predict in forest
2015-04-20 17:27:58 +02:00
4e6346ef62
FIX raise error properly when n_features differ in fit and apply
2015-04-20 17:27:58 +02:00
a5f0159ea5
don't to input validation in each tree for RandomForest.predict
2015-04-13 19:30:02 -04:00
49aa9d5840
Update docstring predict_proba()
2015-03-05 15:33:26 -05:00
feceab6f62
FIX test for consistent handling on empty input data
2015-02-26 10:45:06 +01:00
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
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
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
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
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
Alexandre Gramfort