Resumen de Sedàs: a semantic based general classifier system
A. Valls, D. Riaño, Vicente Torra Ferré
In this work we present the general classifier system Sedàs. We show how this system implements the description of the domain and how it builds similarity matrices and classification trees. The system uses a new semantics, introduced in [Torra96], to define a distance between qualitative values.
