10 min readSupervised Learning
Comparing Classifiers, and What Accuracy Hides
The Bayes classifier nothing can beat and the error floor it leaves behind, k-nearest-neighbours as a nonparametric imitation with k as the flexibility dial, discriminant analysis and why a shared covariance forces a straight line, and the confusion matrix, thresholds and ROC curve that a single accuracy figure conceals - every number computed on simulated data where the optimum is known.
Machine LearningStatistics