weighted.adjacency.matrix

<p>name of the plain text file to be read (<code>def. edges</code>). The format of the file is a sequence of rows.
Each row corresponds to an edge represented through a pair of vertexes (blank separated) and the weight of the edges.
For instance: <code>nodeX nodeY score</code>. The file extension can be plain (".txt") or compressed (".gz").</p>

file

<p>Build a symmetric weighted adjacency matrix (wadj matrix) of a graph.</p>

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>).

weighted.adjacency.matrix: Weighted adjacency matrix

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Examples