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Difference between multi-class and multi-label classification problems. |
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Answer» The classification task in a multi-class classification problem has more than two mutually exclusive classes (classes that have no intersection or no attributes in common), whereas in a multi-LABEL classification problem, each label has a different classification task, although the tasks are related in some way. For example, classifying a group of photographs of ANIMALS that could be cats, dogs, or bears is a multi-class classification problem that assumes each sample can be of only one TYPE, implying that an image can be categorized as either a cat or a DOG, but not both at the same time. Now let us assume you wish to manipulate the image below. The image above must be categorized as both a cat and a dog because it DEPICTS both creatures. A set of labels is allocated to each sample in a multi-label classification issue, and the classes are not mutually exclusive. In a multi-label classification problem, a pattern can belong to one or more classes. |
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