IJGPSampleSearch
The IJGPSampleSearch package performs approxmiate inference in Bayesian networks. The current software computes approximate probability of evidence.
Author
Description
SampleSearch is an importance sampling technique specifically suited for belief networks having zero probabilities. Iterative Join graph propagation (IJGP) is used as a proposal distribution for SampleSearch. A more detailed description can be found in [1].
Input format:
The algorithm uses the Ergo_file_format.
Usage
Call the algorithms as follows:
ijgpss [parameters] -f <ergo-file>
The parameters are detailed below.
Parameters
--task: (int) 0 for computing probability of evidence and 1 for computing updated beliefs (default value is 0)
--ordering: <minfill,topological,mindegree> What ordering to use.
--i-bound: (int) An integer value for the i-bound (default value is 3)
--num-iterations: (int) The maximum number of iterations for which IJGP is run
--outfile (string): The path of the output file (default is out)
--num-samples: (int) The maximum number of samples to be drawn
--time-limt: (int) The maximum time in seconds for which the algorithm is run
--help : Print this help.
Download
A 32-bit Linux executable is available here.
References
[1] SampleSearch: A Scheme that Searches for Consistent Samples. Vibhav Gogate and Rina Dechter. In 11th International Conference on Artificial Intelligence and Statistics (AISTATS), 2007. Link