Which of the following is a common evaluation metric for regression models?

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Question: Which of the following is a common evaluation metric for regression models?

Options:

Correct Answer: Mean Absolute Error

Solution:

Mean Absolute Error (MAE) is a common evaluation metric for regression models, measuring the average magnitude of errors in predictions.

Which of the following is a common evaluation metric for regression models?

Which of the following is a common evaluation metric for regression models?

Step 1: Understand what a regression model is. It is a type of model used to predict continuous values, like prices or temperatures.
Step 2: Know that when we make predictions with a regression model, we want to see how close those predictions are to the actual values.
Step 3: Learn about evaluation metrics, which are tools we use to measure how well our model is performing.
Step 4: One common evaluation metric for regression models is Mean Absolute Error (MAE).
Step 5: MAE calculates the average of the absolute differences between the predicted values and the actual values.
Step 6: A lower MAE value indicates better model performance, meaning the predictions are closer to the actual values.

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