Machine Learning Data Quality

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1 domain-specific abstractions whose origin domain is Machine Learning Data Quality.

• Label noise — Incorrect, inconsistent, ambiguous, or corrupted target labels in supervised-learning data, arising randomly or systematically from annotators, processes, proxies, attacks, or changing definitions.