Package edu.cmu.tetrad.search

Class Bridges

java.lang.Object
edu.cmu.tetrad.search.Bridges
All Implemented Interfaces:
GraphScorer, GraphSearch
public final class Bridges extends Object implements GraphSearch, GraphScorer
GesSearch is an implementation of the GES algorithm, as specified in Chickering (2002) "Optimal structure identification with greedy search" Journal of Machine Learning Research. It works for both BayesNets and SEMs.

Some code optimization could be done for the scoring part of the graph for discrete models (method scoreGraphChange). Some of Andrew Moore's approaches for caching sufficient statistics, for instance.

To speed things up, it has been assumed that variables X and Y with zero correlation do not correspond to edges in the graph. This is a restricted form of the heuristicSpeedup assumption, something GES does not assume. This the graph. This is a restricted form of the heuristicSpeedup assumption, something GES does not assume. This heuristicSpeedup assumption needs to be explicitly turned on using setHeuristicSpeedup(true).

A number of other optimizations were added 5/2015. See code for details.

Author:
Ricardo Silva, Summer 2003, Joseph Ramsey, Revisions 5/2015

  • Constructor Details

    • Bridges

      public Bridges(Score score)
      Construct a Score and pass it in here. The totalScore should return a positive value in case of conditional dependence and a negative values in case of conditional independence. See Chickering (2002), locally consistent scoring criterion. This by default uses all of the processors on the machine.

    • Bridges

      public Bridges(int depth)

  • Method Details

    • setFaithfulnessAssumed

      public void setFaithfulnessAssumed(boolean faithfulnessAssumed)

    • setDepth

      public void setDepth(int depth)

    • search

      public Graph search()
      Specified by:
      search in interface GraphSearch

    • search2

      public Set<Node> search2(Graph graph, List<Node> variables)
      Greedy equivalence search: Start from the empty graph, add edges till model is significant. Then start deleting edges till a minimum is achieved.
      Returns:
      the resulting Pattern.

    • getKnowledge

      public Knowledge getKnowledge()
      Returns:
      the background knowledge.

    • setKnowledge

      public void setKnowledge(Knowledge knowledge)
      Sets the background knowledge.
      Parameters:
      knowledge - the knowledge object, specifying forbidden and required edges.

    • getElapsedTime

      public long getElapsedTime()

    • scoreDag

      public double scoreDag(Graph dag)
      Specified by:
      scoreDag in interface GraphScorer
      Returns:
      the totalScore of the given DAG, up to a constant.

    • getTopGraphs

      public LinkedList<ScoredGraph> getTopGraphs()
      Returns:
      the list of top scoring graphs.

    • setVerbose

      public void setVerbose(boolean verbose)
      Sets whether verbose output should be produced.

    • setMeekVerbose

      public void setMeekVerbose(boolean meekVerbose)
      Sets whether verbose output should be produced.

    • getOut

      public PrintStream getOut()
      Returns:
      the output stream that output (except for log output) should be sent to.

    • setOut

      public void setOut(PrintStream out)
      Sets the output stream that output (except for log output) should be sent to. By detault System.out.

    • getAdjacencies

      public Graph getAdjacencies()
      Returns:
      the set of preset adjacenies for the algorithm; edges not in this adjacencies graph will not be added.

    • setAdjacencies

      public void setAdjacencies(Graph adjacencies)
      Sets the set of preset adjacenies for the algorithm; edges not in this adjacencies graph will not be added.

    • setBoundGraph

      public void setBoundGraph(Graph boundGraph)
      If non-null, edges not adjacent in this graph will not be added.

    • getMaxDegree

      public int getMaxDegree()
      The maximum of parents any nodes can have in output pattern.
      Returns:
      -1 for unlimited.

    • setMaxDegree

      public void setMaxDegree(int maxDegree)
      The maximum of parents any nodes can have in output pattern.
      Parameters:
      maxDegree - -1 for unlimited.

    • setSymmetricFirstStep

      public void setSymmetricFirstStep(boolean symmetricFirstStep)

    • logEdgeBayesFactorsString

      public String logEdgeBayesFactorsString(Graph dag)

    • getNeighbors

      public List<Node> getNeighbors(Graph graph, Node node)

    • setParallelized

      public void setParallelized(boolean parallelized)