Paul R. Yarnold
Optimal Data Analysis, LLC
An optimal model has a specific geometric configuration defined by the number of attributes (“independent variables”—schematically illustrated using circles) and endpoints (defined by response on attribute—indicated by rectangles). Branches direct attributes to endpoints via an if/then/else-based decision rule identified by the (ODA/CTA/novometric) algorithm and operationalized vis-à-vis numerical thresholds or categorical rosters which explicitly maximize (weighted) classification accuracy. In hopes of aiding in the visualization, pursuit and discovery of perfectly accurate statistical classification models, this paper presents schematic diagrams which correspond to combinations of number of attributes and endpoints that are possible for a range of optimal models commonly reported.