Welcome to HEMDAG’s documentation!¶
- implements several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs);
- reconciles flat predictions with the topology of the ontology;
- can enhance the predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes;
- guarantees biologically meaningful predictions that obey the true-path-rule, that is the biological and logical rule that governs the internal coherence of biomedical ontologies;
- is specifically designed for exploiting the hierarchical relationships of DAG-structured taxonomies, such as the Human Phenotype Ontology (
HPO) or the Gene Ontology (
GO), but can be safely applied to tree-structured taxonomies as well (e.g.
FunCat), since trees are DAGs;
- scales nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples;
- provides several utility functions to process and analyze graphs;
- provides several performance metrics to evaluate HEMs algorithms.