AnchorViz: Facilitating Classifier Error Discovery through Interactive Semantic Data Exploration

IUI, pp. 269-280, 2018.

Cited by: 17|Bibtex|Views78
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Other Links: dblp.uni-trier.de|academic.microsoft.com|dl.acm.org

Abstract:

When building a classifier in interactive machine learning, human knowledge about the target class can be a powerful reference to make the classifier robust to unseen items. The main challenge lies in finding unlabeled items that can either help discover or refine concepts for which the current classifier has no corresponding features (i....More

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