📄️ Module 2 Overview
Quick navigation hub for Classification & Evaluation topics covering CV, Logistic Regression, Classification Metrics, Model Comparison, and Decision Boundaries
📄️ Cross-Validation
Complete guide to K-Fold cross-validation, LOOCV, and stratified CV with worked examples and interpretations for CT exam
📄️ Logistic Regression
Complete guide to binary and multi-class logistic regression with sigmoid function, probability interpretation, and worked classification examples for CT exam
📄️ Classification Advanced - Metrics & ROC Curves
ROC curves, AUC, Precision-Recall curves, threshold tuning, and multi-class metrics with worked examples for CT exam
📄️ Model Comparison & Selection
Algorithm comparison framework, performance vs interpretability tradeoffs, and model selection guide for CT exam
📄️ Decision Boundaries
Visual interpretation of classification models, 2D decision boundaries, overfitting vs underfitting, and model-specific boundary shapes