Random Utility Models

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling featured image
Discrete Choice Models

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the …

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A prediction and behavioural analysis of machine learning methods for modelling travel mode choice featured image
Random Utility Models

A prediction and behavioural analysis of machine learning methods for modelling travel mode choice

The emergence of a variety of Machine Learning (ML) approaches for travel mode choice prediction poses an interesting question to transport modellers: which models should be used …

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A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression featured image
Kernel Logistic Regression

A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression

In the last few years, the success of Machine Learning (ML) algorithms has led to the extension of their applications to areas such as transport planning. One of the main tasks …

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