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cs.IR2022★ 2 cited
Impact of Stop Sets on Stopping Active Learning for Text Classification
Luke Kurlandski, Michael Bloodgood
Active learning is an increasingly important branch of machine learning and a powerful technique for natural language processing. The main advantage of active learning is its poten…
cs.IR2020★ 2 cited
Early Forecasting of Text Classification Accuracy and F-Measure with Active Learning
Thomas Orth, Michael Bloodgood
When creating text classification systems, one of the major bottlenecks is the annotation of training data. Active learning has been proposed to address this bottleneck using stopp…