Axiomatization of an exponential similarity function

Article dans une revue: An individual is asked to assess a real-valued variable y based on certain characteristics x = (x1,…, xm), and on a database consisting of n observations of (x1,…, xm, y). A possible approach to combine past observations of x and y with the current values of x to generate an assessment of y is similarity-weighted averaging. It suggests that the predicted value of y, yn+1s, be the weighted average of all previously observed values yi, where the weight of yi is the similarity between the vector xn+11,…, xn+1m, associated with yn+1, and the previously observed vector, xi1,…, xim. This paper axiomatizes, in terms of the prediction yn+1, a similarity function that is a (decreasing) exponential in a norm of the difference between the two vectors compared.

Auteur(s)

Antoine Billot, Itzhak Gilboa, David Schmeidler

Revue
  • Mathematical Social Sciences
Date de publication
  • 2008
Mots-clés
  • Similarity function
  • Axiom
  • Exponential decay
Pages
  • pp.107-115
Version
  • 1
Volume
  • Vol.55,n°2