Using consensus ensembles to identify suspect data
In a consensus ensemble all members must agree before they classify a data point. But even when they all agree some data is still misclassified. In this paper we look closely at consistently misclassified data to investigate whether some of it may be outliers or may have been mislabeled.
Publisher: University of Otago
Series number: 2000/17
Research Type: Discussion Paper