An AI project manager is evaluating different approaches for a credit scoring application. What is the primary advantage of using a random forest over a single decision tree?

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Multiple choice — select the best answer

ALower computational resource requirements
BReduced risk of overfitting to training data
CFaster training and prediction times
DPerfect interpretability of model decisions

✓ Correct answer: B. Reduced risk of overfitting to training data Random forests reduce overfitting by averaging predictions from multiple trees trained on different subsets of data and features. This ensemble approach provides more robust predictions than a single decision tree, which is prone to overfitting to training data.

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An AI project manager is evaluating different approaches for a credit scoring application. What is the primary advantage of using a random forest over a single decision tree?

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