input: from typing import List
  
  def predict_housing_price(living_area: List[int], num_rooms: List[float], prices: List[int]) -> float:
      """Create a Linear Regression model using the given living area and number of rooms to predict housing prices. The model should be trained on the provided data and used to predict the price of a house with given living area and number of rooms.
      >>> predict_housing_price([2000, 1600, 2400, 1400, 3000], [3, 2.5, 3.5, 2, 4], [75000, 43000, 59000, 32000, 85000])
      50000.0
      """
output:     from sklearn.linear_model import LinearRegression
      import numpy as np
  
      X = np.column_stack((living_area, num_rooms))
      y = np.array(prices)
  
      model = LinearRegression()
      model.fit(X, y)
  
      new_house = np.array([[2000, 3]])
      predicted_price = model.predict(new_house)
  
      return predicted_price[0]