Article-Journal

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

PyKernelLogit: Penalised maximum likelihood estimation of Kernel Logistic Regression in Python

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

IoT based monitoring of air quality and traffic using regression analysis

Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach

A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs