Exam Professional Machine Learning Engineer topic 1 question 178 discussion

Existing Custom Model: This approach leverages your already-developed, well-performing model. There's no need to rebuild it using AutoML or BigQuery ML, which might require significant code changes. Vertex Explainable AI (XAI): Vertex AI offers XAI integration with custom models through feature-based attribution methods like sampled Shapley. This provides explanations for each prediction without requiring major modifications to your model code. Sampled Shapley with Baselines: Sampled Shapley is a robust attribution method for explaining model predictions. Using input baselines (like zero values) helps improve the interpretability of explanations, especially for features with large ranges.

According to the documentation at https://cloud.google.com/vertex-ai/docs/explainable-ai/overview, we can utilize both feature-based attribution and sampled Shapley-based explanations. Therefore, for providing explanations for each prediction in a loan classification problem, I believe that feature-based attribution is the optimal approach. Furthermore, updating the custom serving container to include sampled Shapley-based explanations, as suggested in option D, might require more effort, considering that the custom model deployed on Vertex AI already provides this option for explanations.

"minimal effort and provide explanations that are as accurate as possible" this makes the answer C, based on this: https://cloud.google.com/vertex-ai/docs/explainable-ai/improving-explanations

Feature attribution is supported for all types of models (both AutoML and custom-trained), frameworks (TensorFlow, scikit, XGBoost), BigQuery ML models, and modalities (images, text, tabular, video). https://cloud.google.com/vertex-ai/docs/explainable-ai/overview

C you find the answer here https://cloud.google.com/vertex-ai/docs/explainable-ai/overview

pikachu007 answer made me reconsider

Not a deep neural network for sure (B). Out of the remaining 3, A is the simplest approach.

A and B is out because you already have a model, C does not provide an explanation for each prediction. Therefore D meets all the criteria.