[DL-Learner SVN] SF.net SVN: dl-learner:[3416] trunk

[<ji...@us...>]

Revision: 3416
          http://dl-learner.svn.sourceforge.net/dl-learner/?rev=3416&view=rev
Author:   jialva
Date:     2011-11-18 10:02:43 +0000 (Fri, 18 Nov 2011)
Log Message:
-----------
DL-Learner fuzzy extension adapted to new DL-Learner configuration and working properly ;)

Modified Paths:
--------------
    trunk/components-core/src/main/java/org/dllearner/learningproblems/FuzzyPosNegLP.java
    trunk/test/fuzzydll/fuzzytrains.conf

Modified: trunk/components-core/src/main/java/org/dllearner/learningproblems/FuzzyPosNegLP.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/learningproblems/FuzzyPosNegLP.java	2011-11-17 17:39:45 UTC (rev 3415)
+++ trunk/components-core/src/main/java/org/dllearner/learningproblems/FuzzyPosNegLP.java	2011-11-18 10:02:43 UTC (rev 3416)
@@ -20,10 +20,12 @@
 package org.dllearner.learningproblems;
 
 import java.util.Collection;
+import java.util.Iterator;
 import java.util.LinkedList;
 import java.util.Map;
 import java.util.Set;
 import java.util.SortedSet;
+import java.util.TreeSet;
 
 import org.dllearner.core.AbstractLearningProblem;
 import org.dllearner.core.AbstractReasonerComponent;
@@ -61,7 +63,14 @@
 	}
 
 	public void setFuzzyEx(Map<Individual, Double> fuzzyEx) {
-		this.fuzzyEx = fuzzyEx;
+		fuzzyExamples = new TreeSet<FuzzyIndividual>();
+		
+		Iterator it = fuzzyEx.keySet().iterator();		
+		
+		while (it.hasNext()) {
+			Individual i = (Individual) it.next();
+			this.fuzzyExamples.add(new FuzzyIndividual(i.getName(), fuzzyEx.get(i).doubleValue()));
+		}
 	}
 
 	protected boolean useRetrievalForClassification = false;

Modified: trunk/test/fuzzydll/fuzzytrains.conf
===================================================================
--- trunk/test/fuzzydll/fuzzytrains.conf	2011-11-17 17:39:45 UTC (rev 3415)
+++ trunk/test/fuzzydll/fuzzytrains.conf	2011-11-18 10:02:43 UTC (rev 3416)
@@ -19,7 +19,7 @@
 lp.type = "fuzzyPosNeg"
 lp.positiveExamples = { "ex:east1", "ex:east2" }
 lp.negativeExamples = { "ex:west6", "ex:west7" }
-lp.fuzzyEx = [("ex:east1",0.6)]
+lp.fuzzyEx = [("http://www.example.com/fuzzyTrains.owl#east1",1.0),("http://www.example.com/fuzzyTrains.owl#east2",1.0),("http://www.example.com/fuzzyTrains.owl#west6",0.0),("http://www.example.com/fuzzyTrains.owl#west7",0.0)]
 
 // create learning algorithm to run
 alg.type = "Fuzzy CELOE"

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