« Classes in classification tasks » : différence entre les versions

Dernière version du 30 août 2024 à 17:58

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+#REDIRECTION[[Classe]]
-== en construction ==
+[[Catégorie:ENGLISH]]
-[[Catégorie:Vocabulary]]
+==Sources==
-[[Catégorie:Apprentissage machine]]
-[[Catégorie:UNSW]]
-== Définition ==
-XXXXXXXXXXXXXXX
-== Français ==
-'''XXXXXXXXXXXXXXX '''
-== Anglais ==
-'''classes in classification tasks '''
-In a classification task in machine learning, the task is to take each instance and assign it to a particular class. For example, in a machine vision application, the task might involve analysing images of objects on a conveyor belt, and classifying them as ''nuts'', ''bolts'', or other components of some object being assembled. In an optical character recognition task, the task would involve taking instances representing images of characters, and classifying according to which character they are. Frequently in examples, for the sake of simplicity if nothing else, just two classes, sometimes called ''positive'' and ''negative'', are used.
-<small>
 [http://www.cse.unsw.edu.au/~billw/dictionaries/mldict.html      Source : INWS machine learning dictionary]  ]