The Use of Unlabeled Data versus Labeled Data for Stopping Active Learning for Text Classification
TABLE I: Unlabeled data methods for stopping AL. For each dataset, the average number of annotations at the automatically determined stopping points and the average F-measure at the automatically determined stopping points are displayed. Bold entries are statistically significantly different than SP (and non-bold entries are not). The Average row is simply an unweighted macro-average over all the datasets. The final column (labeled “All”) represents standard fully supervised passive learning with the entire set of training data.
['Datasets', 'SP (BV2009/BG2013)', 'SC 2000', 'V 2008', 'LS 2008', 'ZWH 2008', 'ALL']
SP, one of the most widely applicable and easy-to-implement methods, has leading performance, consistent with past findings Accordingly, we use SP as representative of state of the art unlabeled data stopping methods in the rest of our experiments.