Quiz on Decision Trees, Random Forests, and XGBoost

What is the starting point of a Decision Tree called?

• Data Point

• Internal Node

• Root Node

• Leaf Node

What type of prediction does a DecisionTreeClassifier perform?

• Clustering

• Classification

• Regression

• Association

What does Random Forests use to create diverse trees?

• Stacking

• Clustering

• Boosting

• Bagging

What is the main advantage of Random Forests?

• Simple Model

• Easy to Interpret

• High Accuracy

• Low Cost

What does XGBoost use to improve accuracy?

• Sequential Learning

• Random Sampling

• Single Tree

• Static Learning

What is the purpose of the Learning Rate in XGBoost?

• Controls tree depth

• Controls step size

• Controls number of trees

• Controls data sampling

What does Precision measure in model performance?

• All positive cases

• False negatives

• Correct positive predictions

• Overall correct predictions

What is a Leaf Node in a Decision Tree?

• Data split

• Starting point

• Decision point

• Final prediction

What is the main goal of Regression?

• Data association

• Data clustering

• Continuous value prediction

• Categorical prediction

What does Gradient Descent do in XGBoost?

• Maximizes accuracy

• Increases tree depth

• Reduces data size

• Minimizes the loss function