Update id3.py

id3.py

@@ -58,8 +58,7 @@ def fit(self, data, target):
     def _entropy(self, ids):
         # calculate entropy of a node with index ids
         if len(ids) == 0: return 0
-        ids = [i+1 for i in ids]
-        # remove 0 freq since log is not defined at 0 
+        ids = [i+1 for i in ids] # panda series index starts from 1
         freq = np.array(self.target[ids].value_counts())
         return entropy(freq)
 
@@ -83,7 +82,7 @@ def _split(self, node):
             for val in values: 
                 sub_ids = sub_data.index[sub_data[att] == val].tolist()
                 splits.append([sub_id-1 for sub_id in sub_ids])
-            # don't split if a node has too small points
+            # don't split if a node has too small number of points
             if min(map(len, splits)) < self.min_samples_split: continue
             # information gain
             HxS= 0
@@ -124,4 +123,4 @@ def predict(self, new_data):
     y = df.iloc[:, -1]
     tree = DecisionTreeID3(max_depth = 3, min_samples_split = 2)
     tree.fit(X, y)
-    print(tree.predict(X))
+    print(tree.predict(X))