Node Classification

Node classification is a supervised learning task in which a model is trained to predict the class label of a node in a graph based on its features and the labels of its neighboring nodes. This task is commonly used in social network analysis, recommendation systems, and bioinformatics. The goal is to accurately classify nodes based on their attributes and the relationships they have with other nodes in the graph. The model can be trained using various machine learning algorithms such as logistic regression, decision trees, and neural networks. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score.
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