Question 2
Which of the following are challenges in applying Shapley values for model explainability?
Computing Shapley values requires evaluating an exponential number of feature coalitions.
Shapley values assume independence between features, which may not hold in real-world data.
Shapley values are computationally efficient for deep neural networks.
Shapley values provide additive explanations, ensuring the contributions of all features sum up to the model's output.