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Which metric is used to evaluate regression models?

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Question: Which metric is used to evaluate regression models?

Options:

  1. F1 Score
  2. Mean Absolute Error
  3. Precision
  4. Recall

Correct Answer: Mean Absolute Error

Solution: 

Mean Absolute Error (MAE) measures the average magnitude of errors in a set of predictions, without considering their direction, making it a common metric for regression.

Which metric is used to evaluate regression models?

Practice Questions

Q1
Which metric is used to evaluate regression models?
  1. F1 Score
  2. Mean Absolute Error
  3. Precision
  4. Recall

Questions & Step-by-Step Solutions

Which metric is used to evaluate regression models?
  • Step 1: Understand that regression models are used to predict continuous values.
  • Step 2: Learn that we need a way to measure how accurate these predictions are.
  • Step 3: Know that one common metric for this is Mean Absolute Error (MAE).
  • Step 4: Understand that MAE calculates the average of the absolute differences between predicted values and actual values.
  • Step 5: Realize that MAE does not consider whether the predictions are above or below the actual values, only the size of the errors.
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