Decision Trees DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 4)

Questions 16–20

1. 16application · medium

   A data scientist is using the C4.5 algorithm to build a decision tree. The dataset has a mix of numerical and categorical features, and some values are missing. Which characteristic of C4.5 is most relevant to this situation?

   • AIt requires all features to be one-hot encoded.
   • BIt only works with binary splits on numerical features.
   • CIt cannot handle missing values, so they must be imputed first.
   • DIt can handle both numerical and categorical features and supports missing values.
   Reveal Solution Discussion Select an answer first
2. 17foundation · easy

   In a decision tree, what does feature importance typically measure?

   • AThe correlation between the feature and the target variable
   • BThe number of times a feature is used in splits, weighted by the improvement in purity
   • CThe depth at which the feature first appears in the tree
   • DThe number of leaf nodes that use the feature
   Reveal Solution Discussion Select an answer first
4. 18foundation · easy

   How do decision trees typically handle categorical features with multiple categories?

   • ABy converting them to numerical values using label encoding
   • BBy creating binary splits that partition the categories into two groups
   • CBy using one-hot encoding to create a separate branch for each category
   • DBy ignoring categorical features because they cannot be used
   Reveal Solution Discussion Select an answer first
5. 19foundation · easy

   In classification trees, what does Gini impurity measure?

   • AThe probability of misclassifying a randomly chosen element if it were randomly labeled according to the class distribution in the node
   • BThe entropy of the class distribution in the node
   • CThe number of misclassified samples in the node
   • DThe variance of the target variable in the node
   Reveal Solution Discussion Select an answer first
6. 20foundation · easy

   In a decision tree, which component represents the point where a decision is made based on a feature value, leading to a branch?

   • ABranch
   • BLeaf node
   • CInternal node
   • DRoot node
   Reveal Solution Discussion Select an answer first