ungelabelte

Ungelabelte is the inflected German adjective meaning "unlabeled" or "without labels." In everyday usage, it describes objects, items, or data that lack identifying labels or markings. The term can refer to physical objects without product labels, price tags, or brand information, as well as to data that do not carry supervisory annotations.

In data science and machine learning, ungelabelte datasets are those that do not include ground-truth labels for supervision. They are central to unsupervised learning, where structure or patterns are inferred without labels, and to semi-supervised and self-supervised approaches that leverage unlabeled data along with a smaller amount of labeled data.

Handling ungelabelte data involves tasks such as clustering, representation learning, anomaly detection, or learning pretext tasks. When supervised learning is required, ungelabelte data must be paired with labels through annotation, weak supervision, or active learning, which can incur time and cost.

Practical considerations include data quality, distribution shift, and privacy concerns. The term ungelabelte is more common in German-language contexts; in English, the equivalent is "unlabeled data" or "unlabeled objects" depending on the domain.