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Section checkpoint · 06

Tree Models

Use this short test to check whether the main ideas from the section are connected in your mind. A strong score means you can recognise the concepts; revisit linked lessons when an answer feels uncertain.

5questionsTarget: 4/5 or better

Question 11 point

Which concept is most appropriate for this situation: You need a legal separation between data used for learning and data used for estimating generalisation.

Random ForestsRegression TreesClassification TreesDecision Tree Splits

Question 21 point

Which concept is most appropriate for this situation: You need to predict a continuous numeric target and evaluate prediction error.

Bagging and Oob IntuitionRegression TreesClassification TreesFeature Importance Caveats

Question 31 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Pruning and Depth” and explain how its input is transformed into a valid output.

Random ForestsClassification TreesFeature Importance CaveatsPruning and Depth

Question 41 point

Which concept is most appropriate for this situation: You need many decorrelated decision trees whose predictions are aggregated for greater stability.

Random ForestsDecision Tree SplitsRegression TreesBagging and Oob Intuition

Question 51 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Feature Importance Caveats” and explain how its input is transformed into a valid output.

Decision Tree SplitsFeature Importance CaveatsBagging and Oob IntuitionRandom Forests