Feature Engineering and PCA for Binary Classification in R
This article explains how feature engineering and principal component analysis (PCA) can be applied to a two‑feature binary classification problem in R, illustrating data exploration, model evaluation with ROC AUC, and the impact of dimensionality reduction on predictive performance.
