Überwachtes Lernen: Difference between revisions
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==ASE-Definition (engl.)== | ==ASE-Definition (engl.)== | ||
Within the field of machine learning, supervised learning is the most common method. It is used for sorting and grouping information; for this purpose, the artificial intelligence is fed with manually categorized data, on the basis of which the further sorting is performed. The expected, already created, categories represent the output; the input data form the input. The sorted data serves as a set of rules for the application on how to categorize the new data. | Within the field of machine learning, supervised learning is the most common method. It is used for sorting and grouping information; for this purpose, the artificial intelligence is fed with manually categorized data, on the basis of which the further sorting is performed. The expected, already created, categories represent the output; the input data form the input. The sorted data serves as a set of rules for the application on how to categorize the new data. | ||
==Literatur== | ==Literatur== | ||
Latest revision as of 09:32, 4 April 2023
| Überwachtes Lernen | |
|---|---|
| Relevant für Projekte aus der ASE-Initiative | MoSYS |
| Stadium | Up-to-date |
ASE-Definition (dt.)
Innerhalb des Feldes des Machine Learning ist das überwachte Lernen die gängigste Methode. Verwendet wird diese zum Sortieren und Gruppieren von Informationen, dazu wird die Künstliche Intelligenz mit manuell kategorisierten Daten gepflegt, anhand welcher die weiterführende Sortierung vorgenommen wird. Die erwarteten, bereits erstellten, Kategorien stellen den Output dar; die eingegebenen Daten bilden den Input. Die sortierten Daten dienen der Anwendung als Regelwerk, wie die neuen Daten zu kategorisieren sind.
ASE-Definition (engl.)
Within the field of machine learning, supervised learning is the most common method. It is used for sorting and grouping information; for this purpose, the artificial intelligence is fed with manually categorized data, on the basis of which the further sorting is performed. The expected, already created, categories represent the output; the input data form the input. The sorted data serves as a set of rules for the application on how to categorize the new data.
Literatur
WIPO (2019): Artificial Intelligence. WIPO Technology Trends 2019
Siehe auch
| Künstliche Intelligenz, Machine Learning |