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
bc02bd5243
ENH rename decision_paths to decision_path
2015-10-21 17:05:56 +02:00
317281bf22
take glouppe comment
2015-10-21 17:05:55 +02:00
f6d605ff96
Implement decision path in tree
2015-10-21 17:05:55 +02:00
d62e316882
#5322 : Resolving Random Forest build errors (bad input shape)
2015-10-20 10:36:47 -05:00
a5860a1df2
#5322 : Fixed build for tree failures, fixing estimator_checks.check_estimator
2015-10-20 10:36:47 -05:00
7745319e33
#5322 : Added check for DecisionTreeRegressor
2015-10-20 10:34:56 -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
02c0029baa
ENH gbt sparse support
2015-09-28 13:44:12 -07:00
5978c0bbdf
ENH split _tree.pyx into several files
2015-09-09 11:28:24 +02:00
93464798ef
note about variance reduction
2015-07-11 16:03:20 -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
eedc1cddab
Use more natural class_weight="auto" heuristic
2015-06-01 12:49:53 -04:00
64e553398b
DOC document missing attributes
2015-05-12 15:00:38 +02:00
92bda9794f
DOC use same error message in decision tree and random forest
2015-04-20 17:27:58 +02:00
294a6219e2
FIX properly raised not fitted error
2015-04-20 17:27:58 +02:00
4ffbf34588
Factorize input validation
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
29dddc7d30
DOC: better documentation tree.apply
2015-04-11 15:53:41 +02:00
1aa4249bf3
ENH: raise NotFittedError instead of ValueError
2015-04-08 12:16:09 +02:00
28a0994bf2
ENH: public apply method for decision trees
2015-04-08 12:10:27 +02:00
cfe4e15f54
Added tests of apply() for valid and invalid inputs. Fixed style.
2015-04-02 11:15:11 +02:00
fdb42ea4d7
Added indentation to docstring
2015-04-02 11:13:10 +02:00
cb687fd7e4
Added docstring
2015-04-02 11:13:10 +02:00
98dfdc6101
Make apply method of trees public. Added test for concistency with private method.
2015-04-02 11:13:10 +02:00
a13a5859e8
DOC remove sphinx warnings when generating the doc
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and fixes a few other doc problems while I was at it.
The main take-home message is to remember that you need a backslash when
your parameter type description exceeds one line.
2015-03-18 15:49:30 +01:00
6ff4e14395
Update documentation of predict_proba in tree module
2015-03-05 15:33:26 -05:00
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
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
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
b3bdb08964
DOC fix formatting of attributes etc. in docstrings
2014-07-28 19:04:59 +10:00
2fca6ce244
MAINT remove deprecated code from trees and forests
2014-07-22 15:52:48 +02:00
6e2a83b4e1
remove check_arrays stuff and old input validation
2014-07-20 13:31:45 +02:00
c73c9a1c8b
MAINT Re-order argument to put deprecated one at the end
2014-07-12 16:33:28 +02:00
72b3da8302
tree: use min_weight_leaf internally while exposing min_weight_fraction_leaf
2014-07-02 11:47:32 +02:00
7e9c093585
tree: add min_weight_fraction_leaf
2014-07-02 11:47:31 +02:00
bb0689f525
ENH: make trees work with very small max_features.
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Trees do no longer fail if int(max_features*n_features) == 0, but use
max_features=1 if the max_features paramater was larger than 0.0
Fixes #3171 .
2014-06-01 16:34:37 +02:00
d9bd47d51a
Merge pull request #2977 from arjoly/tree-cleanup
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[MRG] Some cleanup in _tree.pyx
2014-03-21 17:38:14 +01:00
Alexandre Gramfort