A Bayesian ARD approach for automatically determining an optimal utility function specification in Discrete Choice Models (DCMs) from an exponentially large set of possible specifications in a purely data-driven manner.
A MATLAB implementation of a Bayesian ARD approach for automatically determining an optimal utility function specification in Discrete Choice Models (DCMs) from an exponentially large set of possible specifications in a purely data-driven manner, as proposed in the paper:
Rodrigues, F., Ortelli, N., Bierlaire, M., Pereira, F. Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models. ArXiv 2019.
A Bayesian ARD approach for automatically determining an optimal utility function specification in Discrete Choice Models (DCMs) from an exponentially large set of possible specifications in a purely data-driven manner.
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