diff --git a/dice_ml/explainer_interfaces/explainer_base.py b/dice_ml/explainer_interfaces/explainer_base.py
index 50ae8e3f..eab7e875 100644
--- a/dice_ml/explainer_interfaces/explainer_base.py
+++ b/dice_ml/explainer_interfaces/explainer_base.py
@@ -532,7 +532,7 @@ def do_posthoc_sparsity_enhancement(self, final_cfs_sparse, query_instance, post
             for feature in features_sorted:
                 # current_pred = self.predict_fn_for_sparsity(final_cfs_sparse.iat[[cf_ix]][self.data_interface.feature_names])
                 # feat_ix = self.data_interface.continuous_feature_names.index(feature)
-                diff = query_instance[feature].iat[0] - int(final_cfs_sparse.at[cf_ix, feature])
+                diff = query_instance[feature].iat[0] - final_cfs_sparse.at[cf_ix, feature]
                 if(abs(diff) <= quantiles[feature]):
                     if posthoc_sparsity_algorithm == "linear":
                         final_cfs_sparse = self.do_linear_search(diff, decimal_prec, query_instance, cf_ix,
@@ -561,17 +561,16 @@ def do_linear_search(self, diff, decimal_prec, query_instance, cf_ix, feature, f
             while((abs(diff) > 10e-4) and (np.sign(diff*old_diff) > 0) and
                   self.is_cf_valid(current_pred)) and (count_steps < limit_steps_ls):
 
-                old_val = int(final_cfs_sparse.at[cf_ix, feature])
+                old_val = final_cfs_sparse.at[cf_ix, feature]
                 final_cfs_sparse.at[cf_ix, feature] += np.sign(diff)*change
                 current_pred = self.predict_fn_for_sparsity(final_cfs_sparse.loc[[cf_ix]][self.data_interface.feature_names])
                 old_diff = diff
 
                 if not self.is_cf_valid(current_pred):
                     final_cfs_sparse.at[cf_ix, feature] = old_val
-                    diff = query_instance[feature].iat[0] - int(final_cfs_sparse.at[cf_ix, feature])
                     return final_cfs_sparse
 
-                diff = query_instance[feature].iat[0] - int(final_cfs_sparse.at[cf_ix, feature])
+                diff = query_instance[feature].iat[0] - final_cfs_sparse.at[cf_ix, feature]
 
                 count_steps += 1
 
@@ -581,7 +580,7 @@ def do_binary_search(self, diff, decimal_prec, query_instance, cf_ix, feature, f
         """Performs a binary search between continuous features of a CF and corresponding values
            in query_instance until the prediction class changes."""
 
-        old_val = int(final_cfs_sparse.at[cf_ix, feature])
+        old_val = final_cfs_sparse.at[cf_ix, feature]
         final_cfs_sparse.at[cf_ix, feature] = query_instance[feature].iat[0]
         # Prediction of the query instance
         current_pred = self.predict_fn_for_sparsity(final_cfs_sparse.loc[[cf_ix]][self.data_interface.feature_names])
@@ -594,7 +593,7 @@ def do_binary_search(self, diff, decimal_prec, query_instance, cf_ix, feature, f
 
         # move the CF values towards the query_instance
         if diff > 0:
-            left = int(final_cfs_sparse.at[cf_ix, feature])
+            left = final_cfs_sparse.at[cf_ix, feature]
             right = query_instance[feature].iat[0]
 
             while left <= right:
@@ -614,7 +613,7 @@ def do_binary_search(self, diff, decimal_prec, query_instance, cf_ix, feature, f
 
         else:
             left = query_instance[feature].iat[0]
-            right = int(final_cfs_sparse.at[cf_ix, feature])
+            right = final_cfs_sparse.at[cf_ix, feature]
 
             while right >= left:
                 current_val = right - ((right - left)/2)