a collection of Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs).


Info: This package contains files in non-standard labels.

conda install

  • linux-64  v2.7.4
  • osx-64  v2.7.4
To install this package with conda run one of the following:
conda install -c bioconda r-hemdag
conda install -c bioconda/label/gcc7 r-hemdag
conda install -c bioconda/label/cf201901 r-hemdag


Documentation Status

HEMDAG library: * 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 always 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 (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.

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