no code implementations • 20 Feb 2023 • Lorena Torres Lahoz, Francisco Camara Pereira, Georges Sfeir, Ioanna Arkoudi, Mayara Moraes Monteiro, Carlos Lima Azevedo
Latent Class Choice Models (LCCM) are extensions of discrete choice models (DCMs) that capture unobserved heterogeneity in the choice process by segmenting the population based on the assumption of preference similarities.
no code implementations • 28 Jan 2021 • Georges Sfeir, Filipe Rodrigues, Maya Abou-Zeid
We present a Gaussian Process - Latent Class Choice Model (GP-LCCM) to integrate a non-parametric class of probabilistic machine learning within discrete choice models (DCMs).
no code implementations • 6 Jul 2020 • Georges Sfeir, Maya Abou-Zeid, Filipe Rodrigues, Francisco Camara Pereira, Isam Kaysi
The proposed model formulates the latent classes using mixture models as an alternative approach to the traditional random utility specification with the aim of comparing the two approaches on various measures including prediction accuracy and representation of heterogeneity in the choice process.