What are performance metrics in AI?
Performance metrics are standards used to evaluate the effectiveness of AI models, such as accuracy, precision, and recall.
Can you explain accuracy and precision?
Accuracy measures the overall correctness of the model, while precision indicates the proportion of true positive results among all positive predictions.
How do I choose the right metrics for my AI project?
Choosing the right metrics depends on your project's goals. For classification tasks, accuracy and F1 score are common, while for regression, you might use RMSE or MAE.
What is F1 score?
The F1 score is the harmonic mean of precision and recall, providing a balance between the two, especially useful in imbalanced datasets.
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