GAME : An hybrid Genetic Algorithm and Expectation-Maximization Approach for Latent Class Modeling. Application to an international comparison of the Internet Technology Acceptance

Alain Cucchi

Conference Papers Year : 2005

GAME : An hybrid Genetic Algorithm and Expectation-Maximization Approach for Latent Class Modeling. Application to an international comparison of the Internet Technology Acceptance

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Alain Cucchi

Function : Author
PersonId : 754497
IdHAL : alain-cucchi
ORCID : 0000-0002-2755-771X

Centre d'Économie et de Management de l'Océan Indien

Keywords

GAME Environnement travail

Domains

Computer Science [cs] Cognitive science

Réunion Univ : Connect in order to contact the contributor

https://hal.univ-reunion.fr/hal-01704178

Submitted on : Thursday, February 8, 2018-12:03:13 PM

Last modification on : Thursday, May 12, 2022-11:22:02 AM

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hal-01704178 , version 1 (08-02-2018)

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HAL Id : hal-01704178 , version 1

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Alain Cucchi. GAME : An hybrid Genetic Algorithm and Expectation-Maximization Approach for Latent Class Modeling. Application to an international comparison of the Internet Technology Acceptance. 12ème Colloque de l’ARSEG, ARSEG - Association des Directeurs de l'Environnement de Travail, Nov 2005, Aix-en-Provence, France. ⟨hal-01704178⟩

GAME : An hybrid Genetic Algorithm and Expectation-Maximization Approach for Latent Class Modeling. Application to an international comparison of the Internet Technology Acceptance

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