235 citations · 274 across the 2 of their papers we have counts for
2 papers
cs.LG2013★ 39 cited
How good is the Electricity benchmark for evaluating concept drift adaptation
Indre Zliobaite
In this correspondence, we will point out a problem with testing adaptive classifiers on autocorrelated data. In such a case random change alarms may boost the accuracy figures. He…
cs.AI2010★ 235 cited
Learning under Concept Drift: an Overview
Indrė Žliobaitė
Concept drift refers to a non stationary learning problem over time. The training and the application data often mismatch in real life problems. In this report we present a context…