Python environment for bayesian learning
pebl <action> [<action parameters>]
Pebl is a Python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations.
Pebl includes the following features:
. Can learn with observational and interventional data . Handles missing values and hidden variables using exact and heuristic methods . Provides several learning algorithms; makes creating new ones simple . Has facilities for transparent parallel execution using several cluster/grid resources . Calculates edge marginals and consensus networks . Presents results in a variety of formats
run <configfile>
Runs pebl based on params in config file.
runtask <picklefile>
Unpickles the file and calls run() on it.
<picklefile> should be a a pickled learner or task.
viewhtml <resultfile> <outputdir>
Creates a html report of the results.
<resultfile> should be a pickled pebl.result.
<outputdir> is where the html files will be placed.
It will be created if it does not exist.
Pebl was written by Abhik Shah <[email protected]>
This manual page was written by Miriam Ruiz <[email protected]>, for the Debian project (but may be used by others).