Question 1
You are training an artificial neural network (ANN) for a regression task to predict house prices. After inspecting the target variable (price) in your dataset, you observe that while most prices fall within a predictable range, there are a handful of extremely expensive mansions and a few properties sold under unusual circumstances that represent severe outliers. Your primary goal is to build a model that performs well on typical houses without letting its predictions be overly influenced by these rare, extreme values. You also desire smoother convergence during training. Which loss function should you primarily consider for this task?
Mean Squared Error
Sum of Squared Errors
Huber Loss
Binary Cross-Entropy Loss