How do I choose the right metric for my model?
An example of an AI chatbot conversation about selecting the best metric for model evaluation.
What factors should I consider when choosing a metric for my model?
You should consider the type of problem (classification or regression), the business objectives, and the data distribution.
Can you explain the difference between accuracy and F1 score?
Accuracy measures the overall correctness, while F1 score balances precision and recall, especially in imbalanced datasets.
When is it better to use AUC-ROC instead of accuracy?
AUC-ROC is better when you need to evaluate the model's performance across different thresholds, especially for imbalanced classes.
What metric should I use for a regression model?
Common metrics for regression include Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared, depending on your goals.
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