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A Gaussian groundplan projection area model for evolving probabilistic classifiers

Theodoridis, T and Agapitos, A and Hu, H (2011) A Gaussian groundplan projection area model for evolving probabilistic classifiers. In: UNSPECIFIED, ? - ?.

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Abstract

In this paper, an investigation of evolvable probabilistic classifiers is conducted, along with a thorough comparison between a classical Gaussian distance model, and the induction of Gaussian-to-circle projection model. The newly introduced model refers to a distance fitness measure, based on the projection of Gaussian distributions with geometric circles. The projection architecture aims to model and classify physical aggressive behaviours, by using biomechanical primitives. The primitives are being used to model the dynamics of the aggressive activities, by evolving biome-chanical classifiers, which can discriminate between three behaviours and six actions. Both evolutionary models have shown strong discrimination performances on recognising the individual actions of each behaviour. From the comparison, the proposed model outperformed the classical one with three ensemble programs. Copyright 2011 ACM.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Genetic and Evolutionary Computation Conference, GECCO'11
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 19 Jan 2015 14:37
Last Modified: 23 Jan 2019 00:17
URI: http://repository.essex.ac.uk/id/eprint/9173

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