MLS-C01 · Question #342
MLS-C01 Question #342: Real Exam Question with Answer & Explanation
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Question
A machine learning (ML) specialist needs to solve a binary classification problem for a marketing dataset. The ML specialist must maximize the Area Under the ROC Curve (AUC) of the algorithm by training an XGBoost algorithm. The ML specialist must find values for the eta, alpha, min_child_weight, and max_depth hyperparameters that will generate the most accurate model. Which approach will meet these requirements with the LEAST operational overhead?
Options
- AUse a bootstrap script to install scikit-learn on an Amazon EMR cluster. Deploy the EMR cluster.
- BDeploy Amazon SageMaker prebuilt Docker images that have scikit-learn installed. Apply k-fold
- CUse Amazon SageMaker automatic model tuning (AMT). Specify a range of values for each
- DSubscribe to an AUC algorithm that is on AWS Marketplace. Specify a range of values for each
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