 Collective classification

Collective classification refers to a set of techniques in machine learning and data mining that focus on the prediction of labels for multiple interrelated instances simultaneously, rather than individually. This approach is particularly useful in domains where instances have dependencies or relationships with each other, such as social networks, citation networks, and biological networks. In traditional classification, each instance is treated independently, and the classification model predicts the label for each instance based solely on its features.