9 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
Large Classification-Risk-Optional Label Acquisition
F. Setoudehtanzangi, Geoffrey J. McLachlan
We study how a limited labeling budget should be allocated to minimize multiclass zero-one classification risk. We consider parametric classification problems in which features are…
Semi-Supervised Classification with Informative Missing Labels in Weibull Mixture Models
Jinran Wu, You-Gan Wang, Geoffrey J. McLachlan
We consider semi-supervised classification from a partially classified sample arising from a two-component Weibull mixture. The feature is observed for all data, whereas some class…
Informative Label Missingness in Multiclass Classification Information Geometry and Excess Risk
Fariborz Setoudehtazang, Geoffrey J. McLachlan
Informative label missingness can change the usual efficiency ordering between completely and partially labelled classifiers because the pattern of missing labels may itself carry…
Informative missingness and its implications in semi-supervised learning
Jinran Wu, You-Gan Wang, Geoffrey J. McLachlan
Semi-supervised learning (SSL) constructs classifiers using both labelled and unlabelled data. It leverages information from labelled samples, whose acquisition is often costly or…