Chapter 4, Microsoft Azure Machine Learning Model Interpretability with SHAP
- Shapley values are model-dependent. (True|False)
False. Shapley values are particularly interesting because they are not ML model dependent.
- Model-agnostic XAI does not require output. (True|False)
False. The output of an ML model is necessary to analyze the contributions of each feature to a result.
- The Shapley value calculates the marginal contribution of a feature in a prediction. (True|False)
True.
- The Shapley value can calculate the marginal contribution of a feature for all of the records in a dataset. (True|False)
True. Each feature can then be compared to the marginal contribution of other features when analyzing the output of an ML model.
- Vectorizing data means that we transform data into numerical vectors. (True|False)
True. This is a key function before running an ML algorithm...