CompTIA DataX (DY0-001) — Question 48

A data scientist is building a model to predict customer credit scores based on information collected from reporting agencies. The model needs to automatically adjust its parameters to adapt to recent changes in the information collected. Which of the following is the best model to use?

Answer options

• A. Decision tree
• B. Random forest
• C. Linear discrimination analysis
• D. XGBoost

Correct answer: D

Explanation

XGBoost is the best choice because it is designed for high performance and can efficiently adapt to changes in the data through its boosting mechanism. Decision trees and random forests are less flexible in adjusting to new data without retraining from scratch, while linear discrimination analysis is not suited for handling complex interactions and non-linear relationships in the data.