Nearest Neighbours & Generative Classification – Practice Quiz

Explore Nearest Neighbours & Generative Classification through 20 original single-select and multiselect questions, from core understanding to worked applications, assumption checks and advanced diagnostic challenges.

Prerequisites: the preceding Statistics curriculum, including probability, conditional distributions, regression, model validation and regularization.

Practice goals: Interpret KNN rules and class-conditional Gaussian parameters; Calculate posterior decisions and compare classifier assumptions; Diagnose imbalance, covariance estimation and dependent features; Evaluate transfer and asymptotic neighborhood choices; Analyze cost-sensitive decisions; Assess the limitations of sparse class-conditional samples. Explanations work through the reasoning and address the alternatives.

Further reading: neighbors; lda_qda; naive_bayes.