--- 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'}