Classifier Chain

Classifier chains are a technique used in multi-label classification, aiming to improve prediction accuracy by explicitly modeling the dependencies between different labels. Current research focuses on optimizing chain order, incorporating advanced algorithms like BERT and gradient boosted trees, and developing methods for explaining the model's predictions, such as Shapley Chains. This approach shows promise in various applications, including sentiment analysis, business text processing, and acoustic event detection, where improved performance over traditional methods has been demonstrated.