Remove irrelevant mention of XGB model

app.py

@@ -310,8 +310,8 @@ with demo:
         Once the server receives the encrypted inputs, it can compute the prediction without ever 
         needing to decrypt any value.
 
-        This server employs an [XGBoost](https://github.com/dmlc/xgboost) classifier model that has 
-        been trained on a synthetic data-set.
+        This server employs a [Decision Tree](https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html)
+        classifier model that has been trained on a synthetic data-set.
         """
     )
 

utils/model.py

@@ -110,8 +110,8 @@ class MultiInputModel:
         assert self._tree_inference is not None, self._is_not_fitted_error_message()
 
         if not self._is_compiled:
-            xgb_inference = self._tree_inference
-            self._tree_inference = lambda *args: xgb_inference(numpy.concatenate(args, axis=1))
+            tree_inference = self._tree_inference
+            self._tree_inference = lambda *args: tree_inference(numpy.concatenate(args, axis=1))
 
         input_names = [f"input_{i}_encrypted" for i in range(len(inputs_encryption_status))]