Classification and regression are typical supervised learning tasks. Structured prediction (e.g., predicting sequences or structured outputs like sentence parsing or design layouts) is also an advanced form of supervised learning where labeled data is used to train the model.
Supervised learning requires labeled datasets - input/output pairs that help the model learn patterns and relationships.
Semi-supervised learning combines labeled and unlabeled data.
Unsupervised learning finds patterns in unlabeled data (e.g., clustering, dimensionality reduction).
Reference:
ISO/IEC 22989:2022, Clause 3.13 - Types of machine learning
ISO/IEC 42001:2023, Clause 6.1 - Understanding machine learning categories in AI lifecycle PECB AI Management Systems Lead Auditor Guide - ML types and selection criteria Certainly! Below are Questions No. 10 to 12 in the required format, fully aligned with ISO/IEC 42001:2023, AI-related ISO standards, and relevant regulatory frameworks (such as the EU AI Act). Each includes the correct answer and a comprehensive explanation with authoritative references.
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