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HEMDAG
View on CRAN: Click
here
Download and install HEMDAG package within the R console
Install from CRAN:
install.packages("HEMDAG")
Install from Github:
library("remotes")
install_github("cran/HEMDAG") Install by package version:
library("remotes")
install_version("HEMDAG", "2.7.4") Attach the package and use:
library("HEMDAG")
Maintained by
Marco Notaro
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-08-11
Latest Update: 2021-02-12
Description:
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) ).
How to cite:
Marco Notaro (2017). HEMDAG: Hierarchical Ensemble Methods for Directed Acyclic Graphs. R package version 2.7.4, https://cran.r-project.org/web/packages/HEMDAG. Accessed 04 Jun. 2026.
Previous versions and publish date:
1.0.0 (2017-08-11 23:56), 1.1.1 (2017-10-16 15:51), 2.0.0 (2018-01-23 11:46), 2.0.1 (2018-02-02 19:32), 2.1.2 (2018-05-07 18:36), 2.1.3 (2018-05-22 00:27), 2.2.3 (2018-08-15 19:40), 2.2.4 (2018-08-19 02:00), 2.2.5 (2018-09-21 18:00), 2.3.6 (2019-03-10 00:13), 2.4.7 (2019-03-18 15:23), 2.4.8 (2019-05-02 23:20), 2.5.9 (2019-10-08 15:50), 2.6.0 (2019-11-15 23:30), 2.6.1 (2020-03-03 23:40), 2.7.3 (2020-09-19 16:20), 2.7.4 (2021-02-12 16:00)
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Other R packages that HEMDAG depends,
imports, suggests or enhances
Complete documentation for HEMDAG
Functions, R codes and Examples using
the HEMDAG R package
Some associated functions: HEMDAG-package . adj.upper.tri . auprc . auroc . build.ancestors . build.children . build.consistent.graph . build.descendants . build.edges.from.hpoo . build.parents . build.scores.matrix . build.subgraph . build.submatrix . check.annotation.matrix.integrity . check.dag.integrity . compute.flipped.graph . constraints.matrix . create.stratified.fold.df . distances.from.leaves . example.datasets . find.best.f . find.leaves . fmax . full.annotation.matrix . gpav.holdout . gpav . gpav.over.examples . gpav.parallel . gpav.vanilla . graph.levels . hierarchical.checkers . htd.holdout . htd . htd.vanilla . lexicographical.topological.sort . multilabel.F.measure . normalize.max . obozinski.heuristic.methods . obozinski.holdout . obozinski.methods . pxr . read.graph . read.undirected.graph . root.node . scores.normalization . specific.annotation.list . specific.annotation.matrix . stratified.cross.validation . tpr.dag.cv . tpr.dag.holdout . tpr.dag . transitive.closure.annotations . tupla.matrix . unstratified.cv.data . weighted.adjacency.matrix . write.graph .
Some associated R codes: annotation.utility.R . gpav.R . graph.utility.R . htd.dag.R . norm.fun.R . obozinski.methods.R . perf.meas.R . pkg.attach.R . pkg.import.R . tpr.dag.R . Full HEMDAG package functions and examples
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