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MLS-C01 · Question #343

MLS-C01 Question #343: Real Exam Question with Answer & Explanation

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Exploratory Data Analysis

Question

A machine learning (ML) developer for an online retailer recently uploaded a sales dataset into Amazon SageMaker Studio. The ML developer wants to obtain importance scores for each feature of the dataset. The ML developer will use the importance scores to feature engineer the dataset. Which solution will meet this requirement with the LEAST development effort?

Options

  • AUse SageMaker Data Wrangler to perform a Gini importance score analysis.
  • BUse a SageMaker notebook instance to perform principal component analysis (PCA).
  • CUse a SageMaker notebook instance to perform a singular value decomposition analysis.
  • DUse the multicollinearity feature to perform a lasso feature selection to perform an importance

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Topics

#SageMaker Data Wrangler#Feature Engineering#Feature Importance#Low-code/No-code ML
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