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What is Exploring Unknown Classes in ML about?

This paper introduces exploratory machine learning (ExML), a new framework designed to address the issue of unknown unknowns in training datasets, where some classes are misperceived due to insufficient feature information. ExML enhances the learning process by actively augmenting the feature space to discover hidden classes while simultaneously classifying known classes. The framework consists of three components: a rejection model, feature exploration, and model cascade, and is validated through theoretic

Author

gsolis.comp

Language

EN