Active Learning für Regressionsprobleme mit Ensemble-Methoden

Untersuchung des Trade-Offs zwischen Qualität und Rechenaufwand

Abstract

Uncertainty estimators are often used for Active Learning (Uncertainty sampling). Depending on the base-model the quality and the computational effort of these estimators can vary. This work explores this trade-off for three different base-models, that are used to build ensembles to get the uncertainty estimates.