Optimal Classification

Optimal classification refers to any method of classification, which inexclusively minimizes the number of queries necessary to identify a particular element within a bounded class.

Table of Contents


Rypka's Method
 * 1) Truth Table Size-Related Equations
 * 2) Separatory Equations
 * 3) Element-Related equations
 * 4) Characteristic-related equations
 * 5) Theoretical separation
 * 6) Empirical separation
 * 7) Target Set Truth Table Values
 * 8) Separation Stages
 * 9) Computational Example
 * 10) Application Example

Specific applications

 * Classification of closed legal cases to help identify new ones
 * Artificial Neural Networks
 * Compute minimum number of hidden nodes
 * Minimize training time
 * Dynamic classification of publications
 * Soil taxonomy