| Status | Subtype | Assigned | Task | ||
|---|---|---|---|---|---|
| Resolved | Halfak | T171505 Late-July 2017 ORES deploy | |||
| Resolved | Ladsgroup | T170960 Add new data for damaging models of Persian Wikipedia | |||
| Resolved | Ladsgroup | T171386 Investigate small loss in fitness with the new data in fawiki |
Event Timeline
Comment Actions
It happened with the goodfaith model here too: T170177: Test draftquality sentiment feature on Editquality
Comment Actions
FYI, for old data and new revscoring version, this is result of damaging:
ScikitLearnClassifier - type: GradientBoosting - params: verbose=0, min_weight_fraction_leaf=0.0, max_leaf_nodes=null, init=null, loss="deviance", min_samples_leaf=1, learning_rate=0.1, n_estimators=300, criterion="friedman_mse", subsample=1.0, min_samples_split=2, max_features="log2", balanced_sample=false, balanced_sample_weight=true, presort="auto", warm_start=false, max_depth=3, min_impurity_split=1e-07, random_state=null, scale=true, center=true - version: 0.3.0 - trained: 2017-07-24T18:57:21.920621 Table: ~False ~True ----- -------- ------- False 18408 927 True 60 182 Accuracy: 0.95 Precision: ----- ----- False 0.997 True 0.164 ----- ----- Recall: ----- ----- False 0.952 True 0.753 ----- ----- PR-AUC: ----- ----- False 0.995 True 0.262 ----- ----- ROC-AUC: ----- ----- False 0.964 True 0.974 ----- ----- Recall @ 0.1 false-positive rate: label threshold recall fpr ------- ----------- -------- ----- False 0.738 0.935 0.084 True 0.079 0.961 0.086 Filter rate @ 0.9 recall: label threshold filter_rate recall ------- ----------- ------------- -------- False 0.961 0.11 0.9 True 0.266 0.924 0.916 Filter rate @ 0.75 recall: label threshold filter_rate recall ------- ----------- ------------- -------- False 0.995 0.259 0.751 True 0.505 0.945 0.76 Recall @ 0.995 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.314 0.967 0.995 True 0.987 0.054 1 Recall @ 0.99 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.058 0.994 0.99 True 0.987 0.054 1 Recall @ 0.98 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.987 0.054 1 Recall @ 0.9 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.987 0.054 1 Recall @ 0.75 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.984 0.071 0.958 Recall @ 0.6 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.975 0.128 0.744 Recall @ 0.45 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.95 0.246 0.489 Recall @ 0.15 precision: label threshold recall precision ------- ----------- -------- ----------- False 0.014 1 0.988 True 0.382 0.848 0.16