Description
Description
Status | Subtype | Assigned | Task | ||
---|---|---|---|---|---|
Resolved | Halfak | T148038 [Epic] Build draft quality model (spam, vandalism, attack, or OK) | |||
Resolved | Halfak | T135644 Generate spam and vandalism new page creation dataset | |||
Resolved | Halfak | T148580 Build feature set for draft quality model | |||
Resolved | Halfak | T148581 Extract features for deleted page (draft quality model) | |||
Resolved | Halfak | T150307 Create manually vetted dataset of spam/vandalism/attack pages | |||
Resolved | Halfak | T151819 Analyze differentiation of FA, Spam, Vandalism, and Attack models/sentences. | |||
Resolved | Halfak | T148037 Generate PCFG sentence models | |||
Resolved | Halfak | T148034 Sentence bank for vandalism | |||
Resolved | Halfak | T148035 Sentence bank for personal attacks | |||
Resolved | Halfak | T148033 Sentence bank for Featured Articles | |||
Resolved | Halfak | T148032 Sentence bank for spam | |||
Resolved | Halfak | T148867 Implement sentences datascources |
Event Timeline
Comment Actions
ScikitLearnClassifier - type: GradientBoosting - params: init=null, scale=false, max_leaf_nodes=null, center=false, warm_start=false, presort="auto", random_state=null, subsample=1.0, max_features="log2", max_depth=7, balanced_sample_weight=false, min_samples_split=2, n_estimators=700, loss="deviance", balanced_sample=false, min_samples_leaf=1, verbose=0, learning_rate=0.01, min_weight_fraction_leaf=0.0 - version: None - trained: 2017-01-17T21:19:14.173403 Table: ~OK ~attack ~spam ~vandalism --------- ----- --------- ------- ------------ OK 24848 5 1078 326 attack 82 249 499 1229 spam 616 14 15915 1154 vandalism 654 209 1813 3827 Accuracy: 0.854 ROC-AUC: ----------- ----- 'OK' 0.983 'attack' 0.93 'spam' 0.97 'vandalism' 0.923 ----------- ----- F1: --------- ----- vandalism 0.587 attack 0.197 OK 0.947 spam 0.86 --------- -----