This paper reviews the mainstream approach to regional classification and suggests a different approach which explicitly recognize the importance of a priori information and of linguistic classification problems. Many techniques of classification rely on the concept of distance to cluster and categories the elements of a set. This paper introdues a more general approach to model regional differences based on the theory of fuzzy sets and on Bayesian inference.
A Bayesian fuzzy approach to model spatial differences: the case of European rural regions / Zanoli, Raffaele; Gambelli, Danilo. - STAMPA. - (1995), p. 765-796. (Intervento presentato al convegno The regional dimension in agricultural economics and policies - 40th seminar CNR-Raisa tenutosi a Ancona nel 26-28th June 1995).
A Bayesian fuzzy approach to model spatial differences: the case of European rural regions
ZANOLI, RAFFAELE;GAMBELLI, Danilo
1995-01-01
Abstract
This paper reviews the mainstream approach to regional classification and suggests a different approach which explicitly recognize the importance of a priori information and of linguistic classification problems. Many techniques of classification rely on the concept of distance to cluster and categories the elements of a set. This paper introdues a more general approach to model regional differences based on the theory of fuzzy sets and on Bayesian inference.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
