Notes on hierarchical ensemble methods for DAG-structured taxonomies
This addresses a niche problem in machine learning for domains like text classification and computational biology, but appears incremental as it extends existing methods from trees to DAGs.
The paper tackles hierarchical multi-label classification for Directed Acyclic Graph (DAG)-structured taxonomies, introducing novel ensemble algorithms like HTD-DAG and TPR-DAG, but does not provide concrete numerical results.
Several real problems ranging from text classification to computational biology are characterized by hierarchical multi-label classification tasks. Most of the methods presented in literature focused on tree-structured taxonomies, but only few on taxonomies structured according to a Directed Acyclic Graph (DAG). In this contribution novel classification ensemble algorithms for DAG-structured taxonomies are introduced. In particular Hierarchical Top-Down (HTD-DAG) and True Path Rule (TPR-DAG) for DAGs are presented and discussed.