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[DL-Learner SVN] SF.net SVN: dl-learner:[1797] trunk/src/dl-learner/org/dllearner
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From: <jen...@us...> - 2009-06-15 06:15:31
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Revision: 1797
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=1797&view=rev
Author: jenslehmann
Date: 2009-06-15 06:14:21 +0000 (Mon, 15 Jun 2009)
Log Message:
-----------
collect more statistical values
Modified Paths:
--------------
trunk/src/dl-learner/org/dllearner/algorithms/celoe/CELOE.java
trunk/src/dl-learner/org/dllearner/scripts/evaluation/OntologyEngineering.java
trunk/src/dl-learner/org/dllearner/utilities/statistics/Stat.java
Modified: trunk/src/dl-learner/org/dllearner/algorithms/celoe/CELOE.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/celoe/CELOE.java 2009-06-15 05:47:44 UTC (rev 1796)
+++ trunk/src/dl-learner/org/dllearner/algorithms/celoe/CELOE.java 2009-06-15 06:14:21 UTC (rev 1797)
@@ -118,7 +118,7 @@
private ConceptComparator descriptionComparator = new ConceptComparator();
// statistical variables
- private int descriptionTests = 0;
+ private int expressionTests = 0;
private int minHorizExp = 0;
private int maxHorizExp = 0;
@@ -283,9 +283,9 @@
}
if (stop) {
- logger.info("Algorithm stopped ("+descriptionTests+" descriptions tested).\n");
+ logger.info("Algorithm stopped ("+expressionTests+" descriptions tested).\n");
} else {
- logger.info("Algorithm terminated successfully ("+descriptionTests+" descriptions tested).\n");
+ logger.info("Algorithm terminated successfully ("+expressionTests+" descriptions tested).\n");
}
// print solution(s)
@@ -345,7 +345,7 @@
// quality of description (return if too weak)
double accuracy = learningProblem.getAccuracyOrTooWeak(description, noise);
- descriptionTests++;
+ expressionTests++;
// System.out.println(description + " " + accuracy);
if(accuracy == -1) {
return false;
@@ -503,7 +503,7 @@
nodes = new TreeSet<OENode>(heuristic);
descriptions = new TreeSet<Description>(new ConceptComparator());
bestEvaluatedDescriptions.getSet().clear();
- descriptionTests = 0;
+ expressionTests = 0;
}
@Override
@@ -582,4 +582,10 @@
return minHorizExp;
}
+ /**
+ * @return the expressionTests
+ */
+ public int getClassExpressionTests() {
+ return expressionTests;
+ }
}
Modified: trunk/src/dl-learner/org/dllearner/scripts/evaluation/OntologyEngineering.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/evaluation/OntologyEngineering.java 2009-06-15 05:47:44 UTC (rev 1796)
+++ trunk/src/dl-learner/org/dllearner/scripts/evaluation/OntologyEngineering.java 2009-06-15 06:14:21 UTC (rev 1797)
@@ -101,6 +101,7 @@
String userInputProtocol = "";
int classCandidatesCount = 0;
Stat instanceCountStat = new Stat();
+ Stat classExpressionTestsStat = new Stat();
// equivalence classes
int candidatesAboveThresholdCount = 0;
@@ -109,6 +110,7 @@
int noSensibleDescriptionCount = 0;
int inconsistencyDetected = 0;
int moreInstancesCount = 0;
+ int nonPerfectCount = 0;
Stat moreInstancesCountStat = new Stat();
Stat accStat = new Stat();
Stat accSelectedStat = new Stat();
@@ -122,6 +124,7 @@
int noSensibleDescriptionCountSC = 0;
int inconsistencyDetectedSC = 0;
int moreInstancesCountSC = 0;
+ int nonPerfectCountSC = 0;
Stat moreInstancesCountStatSC = new Stat();
Stat accStatSC = new Stat();
Stat accSelectedStatSC = new Stat();
@@ -176,7 +179,8 @@
celoe.init();
celoe.start();
-
+ classExpressionTestsStat.addNumber(celoe.getClassExpressionTests());
+
// test whether a solution above the threshold was found
EvaluatedDescription best = celoe.getCurrentlyBestEvaluatedDescription();
double bestAcc = best.getAccuracy();
@@ -295,6 +299,9 @@
moreInstancesCount++;
moreInstancesCountStat.addNumber(additionalInstances);
}
+ if(bestAcc < 0.9999) {
+ nonPerfectCount++;
+ }
} else {
accSelectedStatSC.addNumber(bestAcc);
positionStatSC.addNumber(selectedNr);
@@ -306,6 +313,9 @@
moreInstancesCountSC++;
moreInstancesCountStatSC.addNumber(additionalInstances);
}
+ if(bestAcc < 0.9999) {
+ nonPerfectCountSC++;
+ }
}
}
}
@@ -323,10 +333,12 @@
.println("knowledge engineering process finished successfully - summary shown below");
System.out.println();
System.out.println("ontology: " + args[0]);
+ System.out.println("settings: " + minAccuracy + " min accuracy, " + minInstanceCount + " min instances, " + algorithmRuntimeInSeconds + "s algorithm runtime");
System.out.println("user input protocol: " + userInputProtocol);
System.out.println("classes in ontology: " + classes.size());
System.out.println("classes with at least " + minInstanceCount + " instances: "
+ classCandidatesCount);
+ System.out.println("class expressions tested: " + classExpressionTestsStat.prettyPrint(""));
System.out.println();
System.out.println("statistics for equivalence axioms:");
@@ -334,13 +346,14 @@
+ candidatesAboveThresholdCount);
System.out.println("axioms learned succesfully: " + foundDescriptionCount);
System.out.println("axioms missed: " + missesCount);
- System.out.println("axiom with no sensible axioms: " + noSensibleDescriptionCount);
+ System.out.println("class with no sensible axioms: " + noSensibleDescriptionCount);
System.out.println("average accuracy overall: " + accStat.prettyPrint(""));
System.out.println("average accuracy of selected expressions: "
+ accSelectedStat.prettyPrint(""));
- System.out.println("average accuracy of expressions above threshold "
+ System.out.println("average accuracy of expressions above threshold: "
+ accAboveThresholdStat.prettyPrint(""));
- System.out.println("average number typed by user " + positionStat.prettyPrint(""));
+ System.out.println("non-perfect (not 100% accuracy) axioms selected: " + nonPerfectCount);
+ System.out.println("average number typed by user: " + positionStat.prettyPrint(""));
System.out.println();
System.out.println("statistics for super class axioms:");
@@ -348,13 +361,14 @@
+ candidatesAboveThresholdCountSC);
System.out.println("axioms learned succesfully: " + foundDescriptionCountSC);
System.out.println("axioms missed: " + missesCountSC);
- System.out.println("axiom with no sensible axioms: " + noSensibleDescriptionCountSC);
+ System.out.println("class with no sensible axioms: " + noSensibleDescriptionCountSC);
System.out.println("average accuracy overall: " + accStatSC.prettyPrint(""));
System.out.println("average accuracy of selected expressions: "
+ accSelectedStatSC.prettyPrint(""));
- System.out.println("average accuracy of expressions above threshold "
+ System.out.println("average accuracy of expressions above threshold: "
+ accAboveThresholdStatSC.prettyPrint(""));
- System.out.println("average number typed by user " + positionStatSC.prettyPrint(""));
+ System.out.println("non-perfect (not 100% accuracy) axioms selected: " + nonPerfectCountSC);
+ System.out.println("average number typed by user: " + positionStatSC.prettyPrint(""));
}
@SuppressWarnings("unused")
Modified: trunk/src/dl-learner/org/dllearner/utilities/statistics/Stat.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/statistics/Stat.java 2009-06-15 05:47:44 UTC (rev 1796)
+++ trunk/src/dl-learner/org/dllearner/utilities/statistics/Stat.java 2009-06-15 06:14:21 UTC (rev 1797)
@@ -128,12 +128,16 @@
}
public String prettyPrint(String unit) {
- DecimalFormat df = new DecimalFormat();
- String str = "av. " + df.format(getMean()) + unit;
- str += " (deviation " + df.format(getStandardDeviation()) + unit + "; ";
- str += "min " + df.format(getMin()) + unit + "; ";
- str += "max " + df.format(getMax()) + unit + ")";
- return str;
+ if(sum > 0) {
+ DecimalFormat df = new DecimalFormat();
+ String str = "av. " + df.format(getMean()) + unit;
+ str += " (deviation " + df.format(getStandardDeviation()) + unit + "; ";
+ str += "min " + df.format(getMin()) + unit + "; ";
+ str += "max " + df.format(getMax()) + unit + ")";
+ return str;
+ } else {
+ return "no data collected";
+ }
}
public String prettyPrint(String unit, DecimalFormat df) {
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