publication . Preprint . 2015

Collective decision efficiency and optimal voting mechanisms: A comprehensive overview for multi-classifier models

Georgiou, Harris V.;
Open Access English
  • Published: 07 Feb 2015
A new game-theoretic approach for combining multiple classifiers is proposed. A short introduction in Game Theory and coalitions illustrate the way any collective decision scheme can be viewed as a competitive game of coalitions that are formed naturally when players state their preferences. The winning conditions and the voting power of each player are studied under the scope of voting power indices, as well and the collective competence of the group. Coalitions and power indices are presented in relation to the Condorcet criterion of optimality in voting systems, and weighted Borda count models are asserted as a way to implement them in practice. A special cas...
free text keywords: Computer Science - Computer Science and Game Theory
Download from

L. Kuncheva, “A theoretical study on six classifier fusion strategies”, IEEE Trans. PAMI, Vol.24, No.2, Feb.2002, pp.281-286 N. Ueda, “Optimal linear combination of neural networks for improving classification performance”, IEEE Trans. PAMI, Vil.22, No.2, Feb.2000, pp.207-215. [OpenAIRE]

C.-L. Liu, “Classifier combination based on confidence transformation”, Pat.Rec., 38 (2005), pp.11-28.

J.R. Parker, “Rank and response combination from confusion matrix data”, Inf.Fusion, 2 (2001), pp.113-120.

A. Taylor, W. Zwicker, “Weighted voting, multicameral representation and power”, Games and Econ.Beh., 5 (1993), pp.170-181.

S. Berg, “Indirect voting systems: Banzhaf numbers, majority functions and collective competence”, Eur.J.Pol.Econ., 13 (1997), pp.557-573.

Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue