code: def human__decision_tree():
      
  
      # build data
      N = 1000000
      M = 3
      X = np.zeros((N,M))
      X.shape
      y = np.zeros(N)
      X[0, 0] = 1
      y[0] = 8
      X[1, 1] = 1
      y[1] = 8
      X[2, 0:2] = 1
      y[2] = 4
  
      # fit model
      xor_model = sklearn.tree.DecisionTreeRegressor(max_depth=2)
      xor_model.fit(X, y)
  
      return xor_model
docs: Decision Tree