input: 
  from typing import List, Any
  import numpy as np
  from sklearn import linear_model
  
  def predict_housing_price(data: List[List[float]], living_area: float, rooms: float) -> float:
      """ Train a Linear Regression model using the given data to predict housing prices
      based on living area and number of rooms. Then, use the trained model to predict
      the price of a new house given its living area and number of rooms.
      >>> data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      >>> prices = [75000, 43000, 59000, 32000, 85000]
      >>> living_area = 2200
      >>> rooms = 3
      >>> predict_housing_price(data, living_area, rooms)
      64000.0
      """
      X = np.array([d[:2] for d in data])
      y = np.array([d[2] for d in data])
      model = linear_model.LinearRegression()
      model.fit(X, y)
      return model.predict(np.array([[living_area, rooms]]))[0]
  
output:     X = np.array([d[:2] for d in data])
      y = np.array([d[2] for d in data])
      model = linear_model.LinearRegression()
      model.fit(X, y)
      return model.predict(np.array([[living_area, rooms]]))[0]