input: from typing import List
  
  def predict_house_price(features: List[float]) -> float:
      """ Predict the price of a house given a set of features using a neural network.
      >>> predict_house_price([0.8, 0.4, 0.7])
      # The output should be a float representing the predicted house price,
      # but since this is a placeholder function, we return 0.0 for illustration.
      0.0
      """
      return 0.0
output:     # Placeholder weights for a simple neural network
      weights = [0.5, 0.3, 0.2]
      bias = 0.1
      
      # Simple linear combination of features and weights
      predicted_price = sum(f * w for f, w in zip(features, weights)) + bias
      
      return predicted_price