Welcome to HEMDAG R package!
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- implements several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs);
- reconciles flat predictions with the topology of the ontology;
- can enhance predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes;
- provides biologically meaningful predictions that obey the true-path-rule, 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 (as 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.
Please get a look to the documentation to know how to download, install and make experiments with the HEMDAG package.
If you use HEMDAG, please cite our BMC Bioinformatics article:
M. Notaro, M. Schubach, P. N. Robinson, and G Valentini. Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods. BMC Bioinformatics, 18(1):449, 2017