HEMDAG: Hierarchical Ensemble Methods for Directed Acyclic Graphs
An implementation of several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs). 'HEMDAG' package: 1) reconciles flat predictions with the topology of the ontology; 2) can enhance the predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes; 3) provides biologically meaningful predictions that always obey the true-path-rule, the biological and logical rule that governs the internal coherence of biomedical ontologies; 4) 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; 5) scales nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples; 6) provides several utility functions to process and analyze graphs; 7) provides several performance metrics to evaluate HEMs algorithms. (Marco Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini (2017) <doi:10.1186/s12859-017-1854-y>).
| Version: |
2.7.4 |
| Depends: |
R (≥ 2.10) |
| Imports: |
graph, RBGL, precrec, preprocessCore, methods, plyr, foreach, doParallel, parallel |
| Suggests: |
Rgraphviz, testthat |
| Published: |
2021-02-12 |
| Author: |
Marco Notaro 
[aut, cre],
Alessandro Petrini
[ctb],
Giorgio Valentini
[aut] |
| Maintainer: |
Marco Notaro <marco.notaro at unimi.it> |
| BugReports: |
https://github.com/marconotaro/hemdag/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://hemdag.readthedocs.io
https://github.com/marconotaro/hemdag
https://anaconda.org/bioconda/r-hemdag |
| NeedsCompilation: |
yes |
| Citation: |
HEMDAG citation info |
| Materials: |
NEWS |
| CRAN checks: |
HEMDAG results |
Documentation:
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