Which evaluation metric is best suited for regression tasks?
Practice Questions
Q1
Which evaluation metric is best suited for regression tasks?
Accuracy
F1 Score
Mean Absolute Error
Precision
Questions & Step-by-Step Solutions
Which evaluation metric is best suited for regression tasks?
Step 1: Understand what regression tasks are. Regression tasks involve predicting a continuous value, like predicting the price of a house.
Step 2: Learn about evaluation metrics. These are tools used to measure how well a model is performing.
Step 3: Identify common evaluation metrics for regression. Some common metrics include Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared.
Step 4: Focus on Mean Absolute Error (MAE). MAE calculates the average of the absolute differences between predicted values and actual values.
Step 5: Understand why MAE is useful. It gives a clear idea of how far off predictions are from actual values, without squaring the errors, which can exaggerate larger errors.
