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BIG DATA MINING AND ANALYTICS ISSN2220960654 05/05 pp118144 V o l u m e 2, N u m b e r 2, J u n e 2 0 1 9 DOI: 10.26599/BDMA.2019.9020001Towards Understanding the Security of Modern Image Captchas

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What is biases in machine learning?

Biases in machine learning refer to systematic errors that result from the assumptions made during the machine learning process, leading to distorted predictions or outcomes.

Who is required to file biases in machine learning?

Organizations, companies, or individuals involved in developing or deploying machine learning models are typically required to report biases.

How to fill out biases in machine learning?

Filling out biases in machine learning involves documenting the identified biases in model outcomes, including the methods used for detection and any corrective measures taken.

What information must be reported on biases in machine learning?

Information that must be reported includes the types of biases detected, the data sources used, methodologies for bias assessment, and any remediation strategies employed.

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