input: Write a function to predict housing prices using Linear Regression given the living area and number of rooms. The function should return the predicted price for a given set of features.
  assert housing_price_prediction([[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]], [75000, 43000, 59000, 32000, 85000], [2200, 3]) == 65500.0
  assert housing_price_prediction([[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]], [75000, 43000, 59000, 32000, 85000], [1800, 3]) == 66500.0
  assert housing_price_prediction([[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]], [75000, 43000, 59000, 32000, 85000], [1500, 2]) == 45000.0
  assert housing_price_prediction([], [], [2200, 3]) == None
output: def housing_price_prediction(X, y, features):
      if not X or not y:
          return None
      X = np.array(X)
      y = np.array(y)
      features = np.array(features)
      model = LinearRegression().fit(X, y)
      return model.predict([features])[0]