Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers

The predictive quality of machine learning models is typically measured in terms of their (approximate) expected prediction error or the so-called Area Under the Curve (AUC) for a particular data distribution. However, when the models are constructed by the means of empirical risk minimization, surr...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Ghanbari, Hiva, Scheinberg, Katya
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!