What does accuracy mean in AI models?

What does accuracy mean in AI models?

Accuracy in AI models refers to the proportion of true results (both true positives and true negatives) among the total number of cases examined.

How is accuracy calculated?

Accuracy is calculated using the formula: (True Positives + True Negatives) / Total Population.

Why is accuracy important?

Accuracy is crucial because it indicates how well the model performs in making correct predictions, impacting decision-making.

Are there limitations to using accuracy as a metric?

Yes, accuracy can be misleading, especially in imbalanced datasets where one class dominates.

What are some alternative metrics to consider?

Alternative metrics include precision, recall, F1 score, and AUC-ROC, which provide a more nuanced view of model performance.