Question 14
Domain 2: Explore data and run experimentsWhich of the following is best described by: 'These construct not just one decision tree, but a large number of trees – allowing better predictions on more complex data. Widely used in machine learning and science due to their strong prediction abilities'?
Correct answer: B
Explanation
Ensemble algorithms combine many models, and in this case they "construct not just one decision tree, but a large number of trees" to improve prediction performance. This matches methods like random forests, which use multiple trees to handle "more complex data" and are "widely used in machine learning and science" for strong predictive ability.
Why each option is right or wrong
A. Least Squares Regression
B. Ensemble Algorithms
The description matches an ensemble method under the machine-learning definition in which multiple base learners are trained and combined, rather than relying on a single decision tree; in practice, this is the mechanism used by tree-based ensembles such as random forests and boosting. The key diagnostic phrase is the use of a "large number of trees" to improve predictive performance on complex data, which is exactly the hallmark of ensemble learning rather than a standalone tree model.
C. Dynamic Programming Algorithms
D. Linear Regression