input: from typing import List, Tuple
  
  def predict_housing_price(data: List[Tuple[int, float]], new_house: Tuple[int, float]) -> float:
      """Predict the price of a house given its living area and number of rooms using Linear Regression.
      The model is trained on the provided data.
      >>> data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      >>> predict_housing_price(data, [2200, 3])
      71200.0
      """
      import numpy as np
      from sklearn import linear_model
      
      X = np.array(data)
      y = np.array([75000, 43000, 59000, 32000, 85000])
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      return model.predict([new_house])[0]
output:     import numpy as np
      from sklearn import linear_model
      
      X = np.array([d[:-1] for d in data])
      y = np.array([d[-1] for d in data])
      
      model = linear_model.LinearRegression()
      model.fit(X, y)
      
      return model.predict([new_house[:-1]])[0]