Optimal discriminant analysis and classification tree analysis

Optimal Discriminant Analysis (ODA) and the related classification tree analysis (CTA) are exact statistical methods that maximize predictive accuracy. For any specific sample and exploratory or confirmatory hypothesis, optimal discriminant analysis (ODA) identifies the statistical model that yields maximum predictive accuracy, assesses the exact Type I error rate, and evaluates potential cross-generalizability.

Source: Wikipedia — Optimal discriminant analysis and classification tree analysis (CC BY-SA 4.0)