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Build pipeline for imbalanced classification

DRWMachine Learning Engineer · Online Assessment
MediumMachine Learning EngineerOnline AssessmentML System Design

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This interview question evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer for Build pipeline for imbalanced classification states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Question

Using scikit-learn and imbalanced-learn, build a classification pipeline that handles severe class imbalance, performs standard preprocessing, applies an appropriate resampling method, trains a classifier, and outputs precision, recall, and F1-score on a held-out set.