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huwiki good faith (new merge)
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Authored by awight on Apr 3 2018, 7:17 PM.
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F16634953: huwiki good faith (new merge)
Apr 3 2018, 7:17 PM
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Model Information:
- type: GradientBoosting
- version: 0.4.0
- params: {'max_leaf_nodes': None, 'loss': 'deviance', 'min_weight_fraction_leaf': 0.0, 'population_rates': None, 'scale': True, 'labels': [True, False], 'max_depth': 7, 'n_estimators': 700, 'center': True, 'max_features': 'log2', 'warm_start': False, 'subsample': 1.0, 'min_samples_leaf': 1, 'learning_rate': 0.1, 'presort': 'auto', 'label_weights': OrderedDict([(False, 10)]), 'verbose': 0, 'init': None, 'multilabel': False, 'min_samples_split': 2, 'random_state': None}
Environment:
- revscoring_version: '2.1.0'
- platform: 'Linux-4.9.0-5-amd64-x86_64-with-debian-9.3'
- machine: 'x86_64'
- version: '#1 SMP Debian 4.9.65-3+deb9u2 (2018-01-04)'
- system: 'Linux'
- processor: ''
- python_build: ('default', 'Jan 19 2017 14:11:04')
- python_compiler: 'GCC 6.3.0 20170118'
- python_branch: ''
- python_implementation: 'CPython'
- python_revision: ''
- python_version: '3.5.3'
- release: '4.9.0-5-amd64'
Statistics:
counts (n=37963):
label n ~True ~False
------- ----- --- ------- --------
True 37652 --> 37619 33
False 311 --> 248 63
rates:
True False
---------- ------ -------
sample 0.992 0.008
population 0.992 0.008
match_rate (micro=0.99, macro=0.5):
False True
------- ------
0.002 0.998
filter_rate (micro=0.01, macro=0.5):
False True
------- ------
0.998 0.002
recall (micro=0.993, macro=0.601):
False True
------- ------
0.203 0.999
!recall (micro=0.209, macro=0.601):
False True
------- ------
0.999 0.203
precision (micro=0.991, macro=0.819):
False True
------- ------
0.645 0.994
!precision (micro=0.647, macro=0.819):
False True
------- ------
0.994 0.645
f1 (micro=0.991, macro=0.652):
False True
------- ------
0.308 0.996
!f1 (micro=0.314, macro=0.652):
False True
------- ------
0.996 0.308
accuracy (micro=0.993, macro=0.993):
False True
------- ------
0.993 0.993
fpr (micro=0.791, macro=0.399):
False True
------- ------
0.001 0.797
roc_auc (micro=0.987, macro=0.9):
False True
------- ------
0.812 0.988
pr_auc (micro=0.992, macro=0.682):
False True
------- ------
0.366 0.997
- score_schema: {'properties': {'prediction': {'type': 'bool', 'description': 'The most likely label predicted by the estimator'}, 'probability': {'properties': {'true': 'number', 'false': 'number'}, 'type': 'object', 'description': 'A mapping of probabilities onto each of the potential output labels'}}, 'type': 'object', 'title': 'Scikit learn-based classifier score with probability'}