Merge branch 'feature/fix_metrics' into dev

Author: maks-sh

Readme.rst

@@ -238,9 +238,12 @@ Papers and materials
 9. Zhao, Yan & Fang, Xiao & Simchi-Levi, David. 2017.
     Uplift Modeling with Multiple Treatments and General Response Types. 10.1137/1.9781611974973.66.
 
-10. Nicholas J Radcliffe. 2007
+10. Nicholas J Radcliffe. 2007.
     Using control groups to target on predicted lift: Building and assessing uplift model. Direct Marketing Analytics Journal, (3):14–21, 2007.
 
+11. Devriendt, F., Guns, T., & Verbeke, W. 2020.
+    Learning to rank for uplift modeling. ArXiv, abs/2002.05897.
+
 ===============
 
 Tags

docs/index.rst

@@ -154,9 +154,12 @@ Papers and materials
 9. Zhao, Yan & Fang, Xiao & Simchi-Levi, David. 2017.
     Uplift Modeling with Multiple Treatments and General Response Types. 10.1137/1.9781611974973.66.
 
-10. Nicholas J Radcliffe. 2007
+10. Nicholas J Radcliffe. 2007.
     Using control groups to target on predicted lift: Building and assessing uplift model. Direct Marketing Analytics Journal, (3):14–21, 2007.
 
+11. Devriendt, F., Guns, T., & Verbeke, W. 2020.
+    Learning to rank for uplift modeling. ArXiv, abs/2002.05897.
+
 ===============
 
 Tags

sklift/metrics/__init__.py

@@ -1,11 +1,13 @@
 from .metrics import (
-    uplift_curve, auuc, qini_curve, auqc, uplift_at_k, response_rate_by_percentile,
-    uplift_by_percentile, weighted_average_uplift, treatment_balance_curve,
-    uplift_auc_score, qini_auc_score
+    uplift_curve, perfect_uplift_curve, uplift_auc_score,
+    qini_curve, perfect_qini_curve, qini_auc_score,
+    uplift_at_k, response_rate_by_percentile,
+    weighted_average_uplift, uplift_by_percentile, treatment_balance_curve
 )
 
 __all__ = [
-    uplift_curve, auuc, qini_curve, auqc, uplift_at_k, response_rate_by_percentile,
-    uplift_by_percentile, weighted_average_uplift, treatment_balance_curve,
-    uplift_auc_score, qini_auc_score
+    uplift_curve, perfect_uplift_curve, uplift_auc_score,
+    qini_curve, perfect_qini_curve, qini_auc_score,
+    uplift_at_k, response_rate_by_percentile,
+    weighted_average_uplift, uplift_by_percentile, treatment_balance_curve
 ]