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MLA-C01 · Question #221

An ML engineer is collecting data to train a classification ML model by using Amazon SageMaker AI. The target column can have two possible values: Class A or Class B. The ML engineer wants to ensure t

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Data Preparation for Machine Learning

Question

An ML engineer is collecting data to train a classification ML model by using Amazon SageMaker AI. The target column can have two possible values: Class A or Class B. The ML engineer wants to ensure that the number of samples for both Class A and Class B are balanced, without losing any existing training data. The ML engineer must test the balance of the training data. Which solution will meet this requirement?

Options

  • AUse SageMaker Clarify to check for class imbalance (CI). If the value is equal to 0, then use
  • BUse SageMaker Clarify to check for class imbalance (CI). If the value is greater than 0, then use
  • CUse SageMaker JumpStart to generate a class imbalance (CI) report. If the value is greater than
  • DUse SageMaker JumpStart to generate a class imbalance (CI) report. If the value is equal to 0,

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Topics

#Class Imbalance#SageMaker Clarify#Data Preprocessing#Bias Detection
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