8 citations · 20 across the 6 of their papers we have counts for
3 papers · 1 filter
Identifying Biased Subgroups in Ranking and Classification
Eliana Pastor, Luca de Alfaro, Elena Baralis
When analyzing the behavior of machine learning algorithms, it is important to identify specific data subgroups for which the considered algorithm shows different performance with…
Automating concept-drift detection by self-evaluating predictive model degradation
Tania Cerquitelli, Stefano Proto, Francesco Ventura +2
A key aspect of automating predictive machine learning entails the capability of properly triggering the update of the trained model. To this aim, suitable automatic solutions to s…
Scaling associative classification for very large datasets
Luca Venturini, Elena Baralis, Paolo Garza
Supervised learning algorithms are nowadays successfully scaling up to datasets that are very large in volume, leveraging the potential of in-memory cluster-computing Big Data fram…