Package edu.pitt.dbmi.algo.bayesian.constraint.search

Class PagSamplingRfci

java.lang.Object
edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
All Implemented Interfaces:
IGraphSearch
public class PagSamplingRfci extends Object implements IGraphSearch
Jan 29, 2023 4:10:52 PM
Version:
$Id: $Id
Author:
Kevin V. Bui (kvb2univpitt@gmail.com)

  • Constructor Details

    • PagSamplingRfci

      public PagSamplingRfci(DataSet dataSet)
      Constructor.
      Parameters:
      dataSet - the data set.

  • Method Details

    • search

      public Graph search()
      Runs the search and returns a graph.

      Search for a PAG.

      Specified by:
      search in interface IGraphSearch
      Returns:
      The discovered graph.

    • setNumRandomizedSearchModels

      public void setNumRandomizedSearchModels(int numRandomizedSearchModels)
      Set the number of randomized search models.
      Parameters:
      numRandomizedSearchModels - the number of randomized search models.

    • setVerbose

      public void setVerbose(boolean verbose)
      Set the verbose flag.
      Parameters:
      verbose - the verbose flag.

    • setDepth

      public void setDepth(int depth)
      Set the depth.
      Parameters:
      depth - the depth.

    • setMaxPathLength

      public void setMaxPathLength(int maxPathLength)
      Set the maximum path length.
      Parameters:
      maxPathLength - the maximum path length.

    • setThreshold

      public void setThreshold(boolean threshold)
      Set the threshold.
      Parameters:
      threshold - the threshold.

    • setCutoff

      public void setCutoff(double cutoff)
      Set the cutoff.
      Parameters:
      cutoff - the cutoff.

    • setPriorEquivalentSampleSize

      public void setPriorEquivalentSampleSize(double priorEquivalentSampleSize)
      Set the prior equivalent sample size.
      Parameters:
      priorEquivalentSampleSize - the prior equivalent sample size.

    • setKnowledge

      public void setKnowledge(Knowledge knowledge)
      Set the knowledge.
      Parameters:
      knowledge - the knowledge.