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Exam AWS Certified Machine Learning - Specialty topic 1 question 328 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 328
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A machine learning (ML) specialist at a manufacturing company uses Amazon SageMaker DeepAR to forecast input materials and energy requirements for the company. Most of the data in the training dataset is missing values for the target variable. The company stores the training dataset as JSON files.

The ML specialist develop a solution by using Amazon SageMaker DeepAR to account for the missing values in the training dataset.

Which approach will meet these requirements with the LEAST development effort?

  • A. Impute the missing values by using the linear regression method. Use the entire dataset and the imputed values to train the DeepAR model.
  • B. Replace the missing values with not a number (NaN). Use the entire dataset and the encoded missing values to train the DeepAR model.
  • C. Impute the missing values by using a forward fill. Use the entire dataset and the imputed values to train the DeepAR model.
  • D. Impute the missing values by using the mean value. Use the entire dataset and the imputed values to train the DeepAR model.
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Suggested Answer: B 🗳️
by Peter_Hsieh at March 14, 2024, 9:59 a.m.
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MultiCloudIronMan
6 months, 1 week ago
Selected Answer: B
Best to allow DeepAR to workout the missing value during training. This may allow it to adopt several approaches to find the one with the best fit.
upvoted 1 times
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AIWave
1 year, 1 month ago
Selected Answer: B
DeepAR is a supervised RNNs and is able to handle missing values directly within the model. Instead of pre-processing the data to impute missing values externally, DeepAR can work directly with missing values encoded as NaN.
upvoted 2 times
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KAST_424
1 year, 1 month ago
Selected Answer: B
target—An array of floating-point values or integers that represent the time series. You can encode missing values as null literals, or as "NaN" strings in JSON, or as nan floating-point values in Parquet.
upvoted 2 times
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Peter_Hsieh
1 year, 1 month ago
Selected Answer: B
https://docs.aws.amazon.com/sagemaker/latest/dg/deepar.html
upvoted 3 times
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