Multi-Class Probabilistic Active Learning

by Daniel Kottke, Georg Krempl, Dominik Lang, Johannes Teschner, Myra Spiliopoulou This work addresses active learning for multi-class classification. Active learning algorithms optimize classifier performance by successively selecting the most beneficial instances from a pool of unlabeled instances to be labeled by an oracle. In this work, we study the influence of the following factors […]

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Active Selection of Difficult Classes

by Marianne Stecklina, Tuan Phan Minh, Tim Sabsch, Cornelius Styp von Rekowski, Daniel Kottke, Georg Krempl, Matthias Deliano, Myra Spiliopoulou. In multi-class classification, datasets often contain both classes that can be easily separated from others and classes that require many data to learn an expressive decision boundary from. In active class selection (ACS), the main […]

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