Multi-label classification refers to those classification tasks that have two or more class labels, where one or more class labels may be predicted for each example.
Consider the example of photo classification, where a given photo may have multiple objects in the scene and a model may predict the presence of multiple known objects in the photo, such as “bicycle,” “apple,” “person,” etc.
This is unlike binary classification and multi-class classification, where a single class label is predicted for each example.
- https://machinelearningmastery.com/types-of-classification-in-machine-learning
- https://en.wikipedia.org/wiki/Multi-label_classification
- https://theailearner.com/2019/07/15/multi-label-classification/
- https://medium.com/@saugata.paul1010/a-detailed-case-study-on-multi-label-classification-with-machine-learning-algorithms-and-72031742c9aa