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machine_learning/decision_tree.py

@@ -6,6 +6,7 @@ Output: The decision tree maps a real number input to a real number output.
 import numpy as np
 import doctest
 
+
 class DecisionTree:
     def __init__(self, depth=5, min_leaf_size=5):
         self.depth = depth
@@ -151,6 +152,7 @@ class TestDecisionTree:
 
         return float(squared_error_sum / labels.size)
 
+
 def main():
     """
     In this demonstration first we are generating x which is a numpy array containing values starting