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Authored By
awight
Mar 21 2018, 7:43 PM
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4 KB
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--- master_cswiki_goodfaith_info 2018-03-21 16:10:26.929444030 +0000
+++ simplify_template_cswiki_goodfaith_info 2018-03-21 19:40:49.483231202 +0000
@@ -1,12 +1,12 @@
Model Information:
- type: GradientBoosting
- version: 0.4.0
- - params: {'scale': True, 'subsample': 1.0, 'verbose': 0, 'labels': [True, False], 'random_state': None, 'population_rates': None, 'learning_rate': 0.01, 'init': None, 'presort': 'auto', 'max_leaf_nodes': None, 'min_samples_split': 2, 'multilabel': False, 'n_estimators': 500, 'center': True, 'min_weight_fraction_leaf': 0.0, 'max_features': 'log2', 'min_samples_leaf': 1, 'label_weights': OrderedDict([(False, 10)]), 'loss': 'deviance', 'warm_start': False, 'max_depth': 5}
+ - params: {'scale': True, 'population_rates': None, 'warm_start': False, 'subsample': 1.0, 'presort': 'auto', 'verbose': 0, 'loss': 'deviance', 'label_weights': OrderedDict([(False, 10)]), 'multilabel': False, 'labels': [True, False], 'min_samples_split': 2, 'min_samples_leaf': 1, 'init': None, 'max_depth': 5, 'max_leaf_nodes': None, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'max_features': 'log2', 'center': True, 'random_state': None, 'learning_rate': 0.01}
Environment:
- revscoring_version: '2.1.0'
- - platform: 'Linux-4.9.0-4-amd64-x86_64-with-debian-9.3'
+ - platform: 'Linux-4.9.0-5-amd64-x86_64-with-debian-9.3'
- machine: 'x86_64'
- - version: '#1 SMP Debian 4.9.51-1 (2017-09-28)'
+ - version: '#1 SMP Debian 4.9.65-3+deb9u2 (2018-01-04)'
- system: 'Linux'
- processor: ''
- python_build: ('default', 'Jan 19 2017 14:11:04')
@@ -15,67 +15,67 @@
- python_implementation: 'CPython'
- python_revision: ''
- python_version: '3.5.3'
- - release: '4.9.0-4-amd64'
+ - release: '4.9.0-5-amd64'
Statistics:
- counts (n=19971):
+ counts (n=17802):
label n ~True ~False
------- ----- --- ------- --------
- True 19602 --> 19349 253
- False 369 --> 90 279
+ True 17600 --> 17434 166
+ False 202 --> 102 100
rates:
True False
---------- ------ -------
- sample 0.982 0.018
+ sample 0.989 0.011
population 0.978 0.022
- match_rate (micro=0.949, macro=0.5):
+ match_rate (micro=0.958, macro=0.5):
False True
------- ------
- 0.03 0.97
- filter_rate (micro=0.051, macro=0.5):
+ 0.02 0.98
+ filter_rate (micro=0.042, macro=0.5):
False True
------- ------
- 0.97 0.03
- recall (micro=0.982, macro=0.872):
+ 0.98 0.02
+ recall (micro=0.979, macro=0.743):
False True
------- ------
- 0.756 0.987
- !recall (micro=0.761, macro=0.872):
+ 0.495 0.991
+ !recall (micro=0.506, macro=0.743):
False True
------- ------
- 0.987 0.756
- precision (micro=0.985, macro=0.784):
+ 0.991 0.495
+ precision (micro=0.978, macro=0.768):
False True
------- ------
- 0.574 0.994
- !precision (micro=0.583, macro=0.784):
+ 0.547 0.988
+ !precision (micro=0.557, macro=0.768):
False True
------- ------
- 0.994 0.574
- f1 (micro=0.983, macro=0.822):
+ 0.988 0.547
+ f1 (micro=0.979, macro=0.755):
False True
------- ------
- 0.653 0.991
- !f1 (micro=0.66, macro=0.822):
+ 0.52 0.989
+ !f1 (micro=0.53, macro=0.755):
False True
------- ------
- 0.991 0.653
- accuracy (micro=0.982, macro=0.982):
+ 0.989 0.52
+ accuracy (micro=0.979, macro=0.979):
False True
------- ------
- 0.982 0.982
- fpr (micro=0.239, macro=0.128):
+ 0.979 0.979
+ fpr (micro=0.494, macro=0.257):
False True
------- ------
- 0.013 0.244
- roc_auc (micro=0.979, macro=0.976):
+ 0.009 0.505
+ roc_auc (micro=0.962, macro=0.961):
False True
------- ------
- 0.974 0.979
- pr_auc (micro=0.994, macro=0.875):
+ 0.96 0.962
+ pr_auc (micro=0.989, macro=0.782):
False True
------- ------
- 0.751 0.999
+ 0.565 0.999
- score_schema: {'type': 'object', 'properties': {'probability': {'type': 'object', 'description': 'A mapping of probabilities onto each of the potential output labels', 'properties': {'true': 'number', 'false': 'number'}}, 'prediction': {'type': 'bool', 'description': 'The most likely label predicted by the estimator'}}, 'title': 'Scikit learn-based classifier score with probability'}

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