A prediction in which the model correctly predicts the negative class.
See also:ISO/IEC TR 29119-11:2020 correct reporting of a failure when it is a failure
EXAMPLE The referee correctly awards an offside and so reports a failure to score a goal.
ISTQB - CTAI Syllabus A prediction in which the model correctly predicts the negative class
The open, complete, comprehensible and accessible presentation of information on functional aspects of an AI system. This includes, among other things, the explainability of the AI system (e.g. neural networks), the comprehensibility of the data protection policy, and information about quality assurance processes during development.
ISO/IEC DIS 22989 property of a system that appropriate information about the system is communicated to relevant stakeholders (3.4.13).
Note 1 to entry: Appropriate information for system transparency can include aspects such as features, components, procedures, measures, design goals, design choices and assumptions.
Note 2 to entry: Inappropriate disclosure of some aspects of a system can violate security, privacy, or confidentiality requirements.
ISO/IEC TR 29119-11:2020 level of accessibility to the algorithm (3.1.12) and data used by the AI-based system (3.1.9)
ISTQB - CTAI Syllabus The level of visibility of the algorithm and data used by the AI-based system (After ISO/IEC TR 29119-11)
Transformers serve to convert input information into other output information. Among other things, they are used for various language technology tasks (e.g. translation). Transformers are often implemented as neural networks, in particular as deep learning architectures.
See also:A technique for modifying a pre-trained ML model to perform a different, related task.
ISTQB - CTAI Syllabus A technique for modifying a pre-trained ML model to perform a different related task