SMART: An Open Source Data Labeling Platform for Supervised Learning

December 11, 2018 ยท Declared Dead ยท ๐Ÿ› Journal of machine learning research

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Authors Rob Chew, Michael Wenger, Caroline Kery, Jason Nance, Keith Richards, Emily Hadley, Peter Baumgartner arXiv ID 1812.06591 Category stat.ML: Machine Learning (Stat) Cross-listed cs.LG Citations 12 Venue Journal of machine learning research Last Checked 4 months ago
Abstract
SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks. SMART provides users with an intuitive interface for creating labeled data sets, supports active learning to help reduce the required amount of labeled data, and incorporates inter-rater reliability statistics to provide insight into label quality. SMART is designed to be platform agnostic and easily deployable to meet the needs of as many different research teams as possible. The project website contains links to the code repository and extensive user documentation.
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