update

data_retriever.json

@@ -16,7 +16,6 @@
             "solvers" : [],
             "xtypes" : {
                 "AXp": "Abductive Explanation", "CXp": "Contrastive explanation"}
-
         },
         {
             "ml_type" : "RandomForest",

pages/application/RandomForest/RandomForestComponent.py

@@ -31,13 +31,10 @@ class RandomForestComponent:
         # Conversion model
         options = {}
         if info is not None and '.csv' in type_info:
-            self.data = Dataset(info)
-            self.data.mapping_features()
-            options["n_classes"] = self.data.num_class
-            options["feature_names"] = self.data.feature_names
-            options["n_features"] = self.data.nb_features
-            if isinstance(model, RandomForestClassifier) or isinstance(model, VotingClassifier)\
+            if isinstance(model, RandomForestClassifier) or isinstance(model, VotingClassifier) \
                     or isinstance(model, xrf.rndmforest.RF2001):
+                self.data = Dataset(info)
+                self.data.mapping_features()
                 self.random_forest = XRF(model, self.data)
             elif isinstance(model, XGBRFClassifier):
                 self.random_forest = XGBRandomForest(options, from_model=model)
@@ -70,9 +67,9 @@ class RandomForestComponent:
         self.network = html.Div([])
 
         # Creating a clean and nice text component
-        compt=0
+        compt = 0
         for sample_expl in explanation_result:
-            compt+=1
+            compt += 1
             self.explanation.append(html.H4("Sample{0} : \n".format(compt)))
             for k in sample_expl.keys():
                 self.explanation.append(html.H5(k))