MLS-C01 · Question #394
A finance company has collected stock return data for 5,000 publicly traded companies. A financial analyst has a dataset that contains 2,000 attributes for each company. The financial analyst wants to
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Question
A finance company has collected stock return data for 5,000 publicly traded companies. A financial analyst has a dataset that contains 2,000 attributes for each company. The financial analyst wants to use Amazon SageMaker to identify the top 15 attributes that are most valuable to predict future stock returns. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AUse the linear leaner algorithm in SageMaker to train a linear regression model to predict the stock
- BUse random forest regression in SageMaker to train a model to predict the stock returns. Identify
- CUse an Amazon SageMaker Data Wrangler quick model visualization to predict the stock returns.
- DUse Amazon SageMaker Autopilot to build a regression model to predict the stock returns. Identify
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