pruning
Applied AI interview questions tagged pruning, across every topic.
3 questions · 1 unlocked for you
Concepts behind "pruning"
The curriculum that explains the ideas these questions test.
Foundational
Decision Trees and Splitting CriteriaA decision tree recursively splits the feature space by picking the split that most reduces impurity (Gini or entropy), producing a flowchart you can read top to bottom. Interviews probe trees because they expose whether you understand impurity-based splitting, why depth controls the bias-variance knob, and how a single high-variance tree becomes the building block for random forests and gradient boosting.📊 Evaluation & ML Foundations
Core
BacktrackingBacktracking is systematic search over a tree of partial solutions: at each step you choose an option, explore deeper, and undo the choice before trying the next (choose, explore, unchoose). Pruning kills branches that cannot lead to a valid solution before you waste work on them. Interviews probe it because permutations, combinations, subsets, and constraint problems (N-queens, sudoku) all share this template, and the in-place choose/unchoose pattern avoids re-allocating state at every node, which is the difference between an elegant solution and an exponential memory blowup.💻 Coding & Engineering CraftSign in