Classification: From expert to ensemble to crowd

Article type: Research Article

Authors: Saitta, Lorenza

Affiliations: Università del Piemonte Orientale, Alessandria, Italy

Note: [] Corresponding author: Lorenza Saitta, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy. Tel.: +39 335 6244 153; Fax: +39 0131 360 198; E-mail: saitta@mfn.unipmn.it

Abstract: In this paper a model of the classification task, based on the Monte Carlo theory of stochastic algorithms, is presented. The model allows different classification paradigms to be described, such as the single classifier, the ensemble, and the crowdsourcing ones. Some experimental work validates the theoretical predictions about the relatioship between the mean and variance of the classification accuracy and the number of classifiers.

Keywords: Classification, majority voting, monte carlo algorithms, ensemble classification, crowdsourcing classification

DOI: 10.3233/IA-140065

Journal: Intelligenza Artificiale, vol. 8, no. 1, pp. 3-22, 2014