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)
Do.GPAV.holdout;precision.at.all.recall.levels.single.class (labels are all negatives/positives);precision.at.given.recall.levels.over.classes (labels in a fold are all negatives/positives);do.stratified.cv.data.single.class (sampling of the labels with just one positive/negative);compute.performance to the following high level functions:
Do.TPR.DAG and Do.TPR.DAG.holdout;Do.HTD and Do.HTD.holdout;Do.GPAV and Do.GPAV.holdout;Do.heuristic.methods and Do.heuristic.methods.holdout;lexicographical.topological.sort;precrec package:
precision.at.all.recall.levels.single.class;PXR.at.multiple.recall.levels.over.classes substituted with precision.at.given.recall.levels.over.classes;.txt) or compressed (.gz);CRAN Package Check Results: removed unneeded header and define from GPAV C++ source codeGPAV algorithm (Burdakov et al., Journal of Computational Mathematics, 2006 -- link);GPAV algorithm in the top-down step of the functions TPR.DAG, Do.TPR.DAG and Do.TPR.DAG.holdout;help("HEMDAG-defunct");C++ code of GPAV algorithm;Improved performance metrics:
compute.Fmeasure.multilabel;PXR.at.multiple.recall.levels.over.classes;AUPRC, AUROC, FMM, PXR) can be computed either one-shot or averaged across folds;Improved the high-level hierarchical ensemble functions:
metric: maximization by FMAX or PRC (see manual for further details);do.stratified.cv.data.single.class;Added TPR-DAG: function gathering several hierarchical ensemble variants;
Added Do.TPR.DAG: high-level function to run TPR-DAG cross-validated experiments;
Added Do.TPR.DAG.holdout: high-level functions to run TPR-DAG holdout experiments;
The following TPR-DAG and DESCENS high-level functions were removed:
NOTE: all the removed functions can be run opportunely setting the input parameters of the new high-level function
Do.TPR.DAG(for cross-validated experiments) andDo.TPR.DAG.holdout(for hold-out experiments);
DESCENS algorithm;MAX, AND, OR (Obozinski et al., Genome Biology, 2008 -- link);tupla.matrix function;CITATION file;