input: from typing import List
  
  def predict_house_price(features: List[float]) -> float:
      """
      Predict the price of a house using a neural network given a set of features.
      
      >>> predict_house_price([0.8, 0.4, 0.7])
      >>> # The output will depend on the model's training and the input features.
      """
output:     # Example neural network model (simplified for illustration)
      weights = [0.5, 0.3, 0.2]
      bias = 0.1
      
      # Linear combination of features and weights
      price = sum(f * w for f, w in zip(features, weights)) + bias
      
      return price