vistla: Detecting Influence Paths with Information Theory
Traces information spread through interactions between features, utilising information theory measures and a higher-order generalisation of the concept of widest paths in graphs.
In particular, 'vistla' can be used to better understand the results of high-throughput biomedical experiments, by organising the effects of the investigated intervention in a tree-like hierarchy from direct to indirect ones, following the plausible information relay circuits.
Due to its higher-order nature, 'vistla' can handle multi-modality and assign multiple roles to a single feature.
||R (≥ 3.5.0)
||testthat (≥ 3.0.0)
||Miron B. Kursa
||Miron B. Kursa <m at mbq.me>
||GPL (≥ 3)
Please use the canonical form
to link to this page.