2 papers
cs.LG2024
Confidence Interval Estimation of Predictive Performance in the Context of AutoML
Konstantinos Paraschakis, Andrea Castellani, Giorgos Borboudakis +1
Any supervised machine learning analysis is required to provide an estimate of the out-of-sample predictive performance. However, it is imperative to also provide a quantification…
cs.LG2024
A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML
Giorgos Borboudakis, Paulos Charonyktakis, Konstantinos Paraschakis +1
AutoML platforms have numerous options for the algorithms to try for each step of the analysis, i.e., different possible algorithms for imputation, transformations, feature selecti…