Open Classification

Open classification is a method in machine learning where a system can identify and categorize data points into known classes while also recognizing when a new, unseen class appears. Unlike traditional classifiers limited to predefined categories, open classification allows for the possibility of encountering and handling novel categories, making it adaptable to real-world situations where not all classes are known in advance. This approach is useful for applications like spam detection or content moderation, where new types of content or threats can emerge unexpectedly.