After the data has completed the feature engineering operation, in the process of constructing the model, which of the following options is not a step in the decision tree construction process?

Question

Options

• APruning
• BFeature selection
• CData cleaning
• DDecision tree generation

• A
  7% (4)
• B
  3% (2)
• C
  75% (44)
• D
  15% (9)

Explanation

Data cleaning (C) is not a step in the decision tree construction process because it belongs to the data preprocessing/preparation phase, which occurs before model construction begins. The question explicitly states the data has already completed feature engineering, meaning preprocessing is done.

• A (Pruning) is a core decision tree step - it reduces overfitting by removing branches that have little predictive power after the tree is built.
• B (Feature selection) happens during tree construction - at each node, the algorithm selects the best feature to split on (e.g., using information gain or Gini impurity).
• D (Decision tree generation) is the fundamental construction step - the algorithm recursively partitions the data to grow the tree structure.

Memory tip: Think of the three construction steps as "Select, Generate, Prune" (SGP). Data cleaning is a pre-game activity - it happens in the locker room before the match (model building) even starts.

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