MLS-C01 · Question #390
A data scientist uses Amazon SageMaker Data Wrangler to analyze and visualize data. The data scientist wants to refine a training dataset by selecting predictor variables that are strongly predictive
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Question
A data scientist uses Amazon SageMaker Data Wrangler to analyze and visualize data. The data scientist wants to refine a training dataset by selecting predictor variables that are strongly predictive of the target variable. The target variable correlates with other predictor variables. The data scientist wants to understand the variance in the data along various directions in the feature space. Which solution will meet these requirements?
Options
- AUse the SageMaker Data Wrangler multicollinearity measurement features with a variance inflation
- BUse the SageMaker Data Wrangler Data Quality and Insights Report quick model visualization to
- CUse the SageMaker Data Wrangler multicollinearity measurement features with the principal
- DUse the SageMaker Data Wrangler Data Quality and Insights Report feature to review features by
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