input: from typing import List, Tuple
  
  def predict_house_price(data: List[Tuple[int, float]], target: List[float], new_features: List[Tuple[int, float]]) -> List[float]:
      """Fit a linear regression model to predict housing prices based on living area and number of rooms.
      The model is trained on given data and can then be used to make predictions on new features.
      >>> data = [[2000, 3], [1600, 2.5], [2400, 3.5], [1400, 2], [3000, 4]]
      >>> target = [75000, 43000, 59000, 32000, 85000]
      >>> new_features = [[2200, 3]]
      >>> predict_house_price(data, target, new_features)
      [65000.0]
      """
      import numpy as np
      from sklearn import linear_model
  
      X = np.array(data)
      y = np.array(target)
  
      model = linear_model.LinearRegression()
      model.fit(X, y)
  
      predictions = model.predict(np.array(new_features))
      return predictions.tolist()
output:     import numpy as np
      from sklearn import linear_model
  
      X = np.array(data)
      y = np.array(target)
  
      model = linear_model.LinearRegression()
      model.fit(X, y)
  
      predictions = model.predict(np.array(new_features))
      return predictions.tolist()