Lecture

Discrete choice and machine learning: two methodologies

Description

This lecture explores the complementary methodologies of discrete choice and machine learning, focusing on notations, variables, models, data generating processes, extrapolation, what-if analysis, representativity of the sample, implications, examples, results interpretation, indicators with ML models, research trends, and relevant bibliography.

In MOOCs (2)

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_16tqoy23

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

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