adding calibration methods from abstension package

quapy/CHANGE_LOG.txt

@@ -34,7 +34,10 @@
 - newer versions of numpy raise a warning when accessing types (e.g., np.float). I have replaced all such instances
     with the plain python type (e.g., float).
 
+- new dependency "abstention" (to add to the project requirements and setup)
+
 Things to fix:
+- calibration with recalibration methods has to be fixed for exact_train_prev in EMQ (conflicts with clone, deepcopy, etc.)
 - clean functions like binary, aggregative, probabilistic, etc; those should be resolved via isinstance():
     this is not working; I don't know how to make the isinstance work. Looks like there is some problem with the
     path of the imported class wrt the path of the class that arrives from another module...

quapy/method/aggregative.py

@@ -10,6 +10,7 @@ from sklearn.model_selection import StratifiedKFold, cross_val_predict
 from tqdm import tqdm
 import quapy as qp
 import quapy.functional as F
+from classification.calibration import RecalibratedClassifier
 from quapy.classification.svmperf import SVMperf
 from quapy.data import LabelledCollection
 from quapy.method.base import BaseQuantifier, BinaryQuantifier
@@ -137,6 +138,7 @@ class AggregativeProbabilisticQuantifier(AggregativeQuantifier):
             else:
                 key_prefix = 'base_estimator__'
             parameters = {key_prefix + k: v for k, v in parameters.items()}
+
         self.learner.set_params(**parameters)