From 14c37cbab6d1a4041a1e9482df9b9cbef98fb071 Mon Sep 17 00:00:00 2001
From: Jeffrey Phillips Freeman <jeffrey.freeman@syncleus.com>
Date: Sun, 4 Sep 2011 10:04:05 -0400
Subject: [PATCH] Fixed a bug in the Markov Random Field's joint probability
function causing it to calculate incorrect results.
---
.../graphicalmodel/GraphicalModelNode.java | 1 +
.../SimpleGraphicalModelNode.java | 34 ++++++++++++++++
...stractMarkovRandomFieldAdjacencyGraph.java | 40 ++++---------------
3 files changed, 42 insertions(+), 33 deletions(-)
diff --git a/src/main/java/com/syncleus/dann/graphicalmodel/GraphicalModelNode.java b/src/main/java/com/syncleus/dann/graphicalmodel/GraphicalModelNode.java
index b006bccd..075d9174 100644
--- a/src/main/java/com/syncleus/dann/graphicalmodel/GraphicalModelNode.java
+++ b/src/main/java/com/syncleus/dann/graphicalmodel/GraphicalModelNode.java
@@ -29,5 +29,6 @@ public interface GraphicalModelNode<S> extends XmlSerializable<GraphicalModelNod
S getState();
void learnState();
double stateProbability();
+ double stateProbability(Set<? extends GraphicalModelNode> ignoredInfluences);
void reset();
}
diff --git a/src/main/java/com/syncleus/dann/graphicalmodel/SimpleGraphicalModelNode.java b/src/main/java/com/syncleus/dann/graphicalmodel/SimpleGraphicalModelNode.java
index 5548769c..4e85acdc 100644
--- a/src/main/java/com/syncleus/dann/graphicalmodel/SimpleGraphicalModelNode.java
+++ b/src/main/java/com/syncleus/dann/graphicalmodel/SimpleGraphicalModelNode.java
@@ -107,6 +107,40 @@ public class SimpleGraphicalModelNode<S> extends AbstractContextNode<GraphicalMo
return ((stateEvidence == null) ? 0.0 : stateEvidence.getPercentage(this.state));
}
+ @Override
+ public double stateProbability(Set<? extends GraphicalModelNode> ignoredInfluences)
+ {
+ final Set<GraphicalModelNode> influences = new HashSet<GraphicalModelNode>(this.getInfluencingNodes());
+ influences.removeAll(ignoredInfluences);
+
+ int evidenceOccurrence = 0;
+ int totalOccurrence = 0;
+
+ NextEvidence:
+ for(final Map.Entry<Map<GraphicalModelNode, Object>, StateEvidence<S>> evidenceEntry : this.evidence.entrySet())
+ {
+ final Map<GraphicalModelNode, Object> influencingEvidence = evidenceEntry.getKey();
+ for(GraphicalModelNode influence : influences)
+ {
+ final Object influencingEvidenceState = influencingEvidence.get(influence);
+ if( (influencingEvidenceState == null)||(!influencingEvidenceState.equals(influence.getState())) )
+ continue NextEvidence;
+ }
+
+ final StateEvidence<S> evidence = evidenceEntry.getValue();
+
+ final Integer currentEvidenceOccurrence = evidence.get(this.getState());
+ if( currentEvidenceOccurrence != null )
+ evidenceOccurrence += evidence.get(this.getState());
+ totalOccurrence += evidence.getTotalEvidence();
+ }
+
+ if( totalOccurrence == 0 )
+ return 0.0;
+
+ return ((double)evidenceOccurrence) / ((double)totalOccurrence);
+ }
+
private Map<GraphicalModelNode, Object> getInfluencingStates()
{
//TODO change this so it only cares if it has edges to work with and doesnt care what networks its a part of
diff --git a/src/main/java/com/syncleus/dann/graphicalmodel/markovrandomfield/AbstractMarkovRandomFieldAdjacencyGraph.java b/src/main/java/com/syncleus/dann/graphicalmodel/markovrandomfield/AbstractMarkovRandomFieldAdjacencyGraph.java
index faa4aa40..829c6665 100644
--- a/src/main/java/com/syncleus/dann/graphicalmodel/markovrandomfield/AbstractMarkovRandomFieldAdjacencyGraph.java
+++ b/src/main/java/com/syncleus/dann/graphicalmodel/markovrandomfield/AbstractMarkovRandomFieldAdjacencyGraph.java
@@ -43,42 +43,16 @@ public abstract class AbstractMarkovRandomFieldAdjacencyGraph<N extends Graphica
@Override
public double jointProbability()
{
- //first we need to preserve a map of all the starting states so we can reset the network back to its starting
- //point when we are done
- Map<N, Object> startingStates = new HashMap<N, Object>();
- for(N node : this.getNodes())
- startingStates.put(node, node.getState());
-
- try
+ final Set<N> seenNodes = new HashSet<N>();
+ double probabilityProduct = 1.0;
+ for(final N node : this.getNodes())
{
- final Set<N> seenNodes = new HashSet<N>();
- double probabilityProduct = 1.0;
- for(final N node : this.getNodes())
- {
- assert !seenNodes.contains(node);
-
- //if none of its neighbors have been seen, then calculate it normally
- final Set<N> nodesToVary = new HashSet<N>(seenNodes);
- nodesToVary.retainAll(this.getAdjacentNodes(node));
- resetNodeStates(nodesToVary);
- double nodeStateProbability = 0.0;
- do
- {
- nodeStateProbability += node.stateProbability();
- }
- while( !incrementNodeStates(nodesToVary) );
+ assert !seenNodes.contains(node);
- seenNodes.add(node);
+ probabilityProduct *= node.stateProbability(seenNodes);
- probabilityProduct *= nodeStateProbability;
- }
- return probabilityProduct;
- }
- finally
- {
- //restore the initial states when we are done
- for(Map.Entry<N,Object> nodeState : startingStates.entrySet())
- nodeState.getKey().setState(nodeState.getValue());
+ seenNodes.add(node);
}
+ return probabilityProduct;
}
}
\ No newline at end of file
--
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