Optimize model with superior feature engineering

Superior feature engineering involves crafting insightful, relevant, and discriminative features from raw data to enhance model performance. It goes beyond basic data preprocessing by extracting meaningful patterns, transforming variables to better fit model assumptions, and selecting pertinent input variables. This process not only optimizes predictive accuracy but also improves model interpretability and robustness.

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