diff --git a/KDEy/kdey_devel.py b/KDEy/kdey_devel.py
index 57cc487..c7fc237 100644
--- a/KDEy/kdey_devel.py
+++ b/KDEy/kdey_devel.py
@@ -326,7 +326,7 @@ class KDEyMLauto2(KDEyML):
                 if self.target == 'likelihood':
                     loss_fn = neg_loglikelihood_prev
                 else:
-                    loss_fn = lambda prev_hat: qp.error.from_name(self.target)(prev, prev_hat)
+                    loss_fn = lambda prev_hat: qp.error.from_name(self.target)(prevtrue, prev_hat)
 
                 pred_prev, neglikelihood = optim_minimize(loss_fn, init_prev, return_loss=True)
                 loss_accum += neglikelihood
diff --git a/KDEy/quantification_evaluation.py b/KDEy/quantification_evaluation.py
index b35dfe8..7591783 100644
--- a/KDEy/quantification_evaluation.py
+++ b/KDEy/quantification_evaluation.py
@@ -43,7 +43,7 @@ METHODS = [
     ('KDEy-AE',  KDEyMLauto2(newLR(), bandwidth='auto', target='mae', search='grid'), wrap_hyper(logreg_grid)),
     ('KDEy-AE+',  KDEyMLauto2(newLR(), bandwidth='auto', target='mae', search='optim'), wrap_hyper(logreg_grid)),
     ('KDEy-RAE',  KDEyMLauto2(newLR(), bandwidth='auto', target='mrae', search='grid'), wrap_hyper(logreg_grid)),
-    ('KDEy-RAE',  KDEyMLauto2(newLR(), bandwidth='auto', target='mrae', search='optim'), wrap_hyper(logreg_grid)),
+    ('KDEy-RAE+',  KDEyMLauto2(newLR(), bandwidth='auto', target='mrae', search='optim'), wrap_hyper(logreg_grid)),
 ]
 
 
@@ -167,4 +167,4 @@ if __name__ == '__main__':
     for method_name, quantifier, param_grid in METHODS + TRANSDUCTIVE_METHODS:
         run_experiment(method_name, quantifier, param_grid)
 
-    show_results(global_result_path)
\ No newline at end of file
+    show_results(global_result_path)