adding class_weight_target property

toolkit.py

@@ -2038,6 +2038,7 @@ class ClassificationProjectDecorr(ClassificationProject):
         self._class_output = None
         self._adv_outputs = None
         self._model_adv = None
+        self._class_weight_target = None
 
 
     def load(self, *args, **kwargs):
@@ -2059,6 +2060,26 @@ class ClassificationProjectDecorr(ClassificationProject):
             )
 
 
+    @property
+    def class_weight_target(self):
+        if self._class_weight_target is None:
+            self._class_weight_target = []
+            for var_i, binning in enumerate(self.decorr_binnings, 1):
+                sumw = self.w_train[self.l_train==0].sum()
+                class_weight = [
+                    sumw/(
+                    len(binning)
+                    * self.w_train[
+                        (np.argmax(self.get_output_list(self.y_train)[var_i], axis=1) == label)
+                        & (self.l_train == 0)
+                    ].sum()
+                    )
+                    for label in range(len(binning))
+                ]
+                self._class_weight_target.append(class_weight)
+        return self._class_weight_target
+
+
     def get_output_list(self, y):
         out_list = super(ClassificationProjectDecorr, self).get_output_list(y)
         for i, (out, binning) in enumerate(