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Delves into the complementary methodologies of discrete choice and machine learning, covering notations, variables, models, data processes, extrapolation, what-if analysis, and more.
Explores latent classes in mixture models for discrete choice modeling using the Swissmetro dataset, discussing class-specific models and random parameters estimation.
