Exam CFE-201 Ch.11: Machine learning, predictive analytics, and model evaluation | Actuarial Village

Exam CFE-201: Corporate Finance — Chapter 11: Machine learning, predictive analytics, and model evaluation

Key concepts covered:
• Precision asks: when the model predicts positive, how often is it right?
• Recall asks: of all actual positives, how many did the model capture?
• Specificity asks: of all actual negatives, how many did it correctly reject?
• Accuracy asks: what fraction of all predictions were correct?
• False positive rate asks: how often does the model wrongly flag negatives?

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