Society of Actuaries (SOA) PA Practice Exam

Why are boosted trees used in business problems?

1. Because they simplify the decision-making process

2. Because they enhance the interpretability of models

3. Because they combine weak learners to form a strong learner

4. Because they operate independently without needing a sequence

The correct answer is: Because they combine weak learners to form a strong learner

Boosted trees are used in business problems primarily because they combine weak learners to form a strong learner. This is achieved through an ensemble learning technique where multiple simple models (weak learners), such as decision trees, are trained sequentially. Each new tree is built to correct the errors made by the previous trees, allowing the ensemble to produce a robust model that often outperforms individual models. Through this iterative process, boosted trees are able to capture complex patterns in the data and improve predictive accuracy. The method works particularly well in scenarios with complex relationships in the data, making it a valuable tool for tackling various business challenges like customer segmentation, risk assessment, and fraud detection. Other options discuss aspects like simplifying decision-making, enhancing interpretability, and operating independently. However, while these factors may play roles in the broader context of model selection or application, they do not specifically capture the core strength of boosted trees in creating a more accurate predictive model through the combination of weak learners.