Multi-label classification
Multi-label classification is a classification task where each instance can be assigned to multiple classes or labels simultaneously. In other words, an instance can belong to more than one category or have multiple attributes. For example, a movie can belong to multiple genres, such as action, comedy, and romance. Similarly, an image can have multiple objects in it (Figure 6.14):
Figure 6.14 – Multi-label image classification with prediction probabilities shown
But how is it different from multi-class classification? Multi-class classification is a classification task where each instance can be assigned to only one class or label. In this case, the classes or categories are mutually exclusive, meaning an instance can belong to just one category. For example, a handwritten digit recognition task would be multi-class since each digit can belong to only one class (0-9).
In summary, the main difference between multi-label...
