#rare-class-detection News & Analysis

Improving Detection of Rare Nodes in Hierarchical Multi-Label Learning

Researchers propose a weighted loss function for neural networks that improves detection of rare hierarchical classes in multi-label classification tasks. By combining node-wise imbalance weighting with focal weighting based on ensemble uncertainties, the approach achieves up to 5x recall improvements and significant F1 score gains on benchmark datasets.