Menu
▾
▴
[DL-Learner SVN] SF.net SVN: dl-learner:[2336] trunk
|
From: <jen...@us...> - 2010-09-24 12:49:03
|
Revision: 2336
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=2336&view=rev
Author: jenslehmann
Date: 2010-09-24 12:48:56 +0000 (Fri, 24 Sep 2010)
Log Message:
-----------
cross validation slightly extended; pred. acc. approximation for class learning
Modified Paths:
--------------
trunk/components-core/src/main/java/org/dllearner/learningproblems/ClassLearningProblem.java
trunk/scripts/src/main/java/org/dllearner/scripts/CrossValidation.java
Modified: trunk/components-core/src/main/java/org/dllearner/learningproblems/ClassLearningProblem.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/learningproblems/ClassLearningProblem.java 2010-09-24 12:08:03 UTC (rev 2335)
+++ trunk/components-core/src/main/java/org/dllearner/learningproblems/ClassLearningProblem.java 2010-09-24 12:48:56 UTC (rev 2336)
@@ -21,6 +21,7 @@
import java.util.Collection;
import java.util.Collections;
+import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;
@@ -463,6 +464,62 @@
return heuristic.equals(HeuristicType.FMEASURE) ? getFMeasure(recall, precision) : Heuristics.getAScore(recall, precision, coverageFactor);
+ } else if(heuristic.equals(HeuristicType.FMEASURE)) {
+ int maxNotCovered = (int) Math.ceil(noise*classInstances.size());
+
+ int notCoveredPos = 0;
+// int notCoveredNeg = 0;
+
+ int posClassifiedAsPos = 0;
+ int negClassifiedAsNeg = 0;
+
+ int nrOfPosChecks = 0;
+ int nrOfNegChecks = 0;
+
+ // special case: we test positive and negative examples in turn
+ Iterator<Individual> itPos = classInstances.iterator();
+ Iterator<Individual> itNeg = superClassInstances.iterator();
+
+ do {
+ // in each loop we pick 0 or 1 positives and 0 or 1 negative
+ // and classify it
+
+ if(itPos.hasNext()) {
+ Individual posExample = itPos.next();
+// System.out.println(posExample);
+
+ if(reasoner.hasType(description, posExample)) {
+ posClassifiedAsPos++;
+ } else {
+ notCoveredPos++;
+ }
+ nrOfPosChecks++;
+
+ // take noise into account
+ if(notCoveredPos > maxNotCovered) {
+ return -1;
+ }
+ }
+
+ if(itNeg.hasNext()) {
+ Individual negExample = itNeg.next();
+ if(!reasoner.hasType(description, negExample)) {
+ negClassifiedAsNeg++;
+ }
+ nrOfNegChecks++;
+ }
+
+ // compute how accurate our current approximation is and return if it is sufficiently accurate
+ double approx[] = Heuristics.getPredAccApproximation(classInstances.size(), superClassInstances.size(), 1, nrOfPosChecks, posClassifiedAsPos, nrOfNegChecks, negClassifiedAsNeg);
+ if(approx[1]<approxDelta) {
+// System.out.println(approx[0]);
+ return approx[0];
+ }
+
+ } while(itPos.hasNext() || itNeg.hasNext());
+
+ double ret = Heuristics.getPredictiveAccuracy(classInstances.size(), superClassInstances.size(), posClassifiedAsPos, negClassifiedAsNeg, 1);
+ return ret;
} else {
throw new Error("Approximation for " + heuristic + " not implemented.");
}
Modified: trunk/scripts/src/main/java/org/dllearner/scripts/CrossValidation.java
===================================================================
--- trunk/scripts/src/main/java/org/dllearner/scripts/CrossValidation.java 2010-09-24 12:08:03 UTC (rev 2335)
+++ trunk/scripts/src/main/java/org/dllearner/scripts/CrossValidation.java 2010-09-24 12:48:56 UTC (rev 2336)
@@ -41,9 +41,9 @@
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.owl.Description;
import org.dllearner.core.owl.Individual;
+import org.dllearner.learningproblems.Heuristics;
import org.dllearner.learningproblems.PosNegLP;
import org.dllearner.learningproblems.PosOnlyLP;
-import org.dllearner.parser.ParseException;
import org.dllearner.utilities.Helper;
import org.dllearner.utilities.datastructures.Datastructures;
import org.dllearner.utilities.statistics.Stat;
@@ -64,6 +64,8 @@
private Stat accuracy = new Stat();
private Stat length = new Stat();
private Stat accuracyTraining = new Stat();
+ private Stat fMeasure = new Stat();
+ private Stat fMeasureTraining = new Stat();
public static void main(String[] args) {
File file = new File(args[0]);
@@ -261,6 +263,17 @@
double currAccuracy = 100*((double)correctExamples/(testSetsPos.get(currFold).size()+
testSetsNeg.get(currFold).size()));
accuracy.addNumber(currAccuracy);
+ // calculate training F-Score
+ int negAsPosTraining = rs.hasType(concept, trainingSetsNeg.get(currFold)).size();
+ double precisionTraining = trainingCorrectPosClassified + negAsPosTraining == 0 ? 0 : trainingCorrectPosClassified / (double) (trainingCorrectPosClassified + negAsPosTraining);
+ double recallTraining = trainingCorrectPosClassified / (double) trainingSetsPos.get(currFold).size();
+ fMeasureTraining.addNumber(100*Heuristics.getFScore(recallTraining, precisionTraining));
+ // calculate test F-Score
+ int negAsPos = rs.hasType(concept, testSetsNeg.get(currFold)).size();
+ double precision = correctPosClassified + negAsPos == 0 ? 0 : correctPosClassified / (double) (correctPosClassified + negAsPos);
+ double recall = correctPosClassified / (double) testSetsPos.get(currFold).size();
+// System.out.println(precision);System.out.println(recall);
+ fMeasure.addNumber(100*Heuristics.getFScore(recall, precision));
length.addNumber(concept.getLength());
@@ -282,8 +295,11 @@
System.out.println("Finished " + folds + "-folds cross-validation on " + file + ".");
System.out.println("runtime: " + statOutput(df, runtime, "s"));
System.out.println("length: " + statOutput(df, length, ""));
- System.out.println("accuracy: " + statOutput(df, accuracy, "%"));
- System.out.println("accuracy on training set: " + statOutput(df, accuracyTraining, "%"));
+ System.out.println("F-Measure on training set: " + statOutput(df, fMeasureTraining, "%"));
+ System.out.println("F-Measure: " + statOutput(df, fMeasure, "%"));
+ System.out.println("predictive accuracy on training set: " + statOutput(df, accuracyTraining, "%"));
+ System.out.println("predictive accuracy: " + statOutput(df, accuracy, "%"));
+
}
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
