What are the key performance metrics for algorithms?
Key performance metrics for algorithms include accuracy, precision, recall, F1 score, and AUC-ROC.
Can you explain accuracy and how it's calculated?
Accuracy is the ratio of correctly predicted instances to the total instances. It's calculated as (TP + TN) / (TP + TN + FP + FN).
What is the difference between precision and recall?
Precision measures the accuracy of positive predictions, while recall measures the ability to find all positive instances.
How do I choose the right metric for my algorithm?
Choosing the right metric depends on your specific problem. For example, use precision for imbalanced classes and recall for critical positive cases.
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