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Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 4: Data quality process framework
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STANDARD published on 15.7.2024
Designation standards: ISO/IEC 5259-4-ed.1.0
Publication date standards: 15.7.2024
SKU: NS-1192096
The number of pages: 28
Approximate weight : 84 g (0.19 lbs)
Country: International technical standard
Category: Technical standards ISO
This document establishes general common organizational approaches, regardless of the type, size or nature of the applying organization, to ensure data quality for training and evaluation in analytics and machine learning (ML). It includes guidance on the data quality process for:
— supervised ML with regard to the labelling of data used for training ML systems, including common organizational approaches for training data labelling;
— unsupervised ML;
— semi-supervised ML;
— reinforcement learning;
— analytics.
This document is applicable to training and evaluation data that come from different sources, including data acquisition and data composition, data preparation, data labelling, evaluation and data use. This document does not define specific services, platforms or tools.
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Latest update: 2024-08-30 (Number of items: 2 345 304)
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