Ricardo García-Ródenas

Recientes

• A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
• IoT based monitoring of air quality and traffic using regression analysis
• A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
• 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
• Discrete choice modeling using Kernel Logistic Regression