[DL-Learner SVN] SF.net SVN: dl-learner:[2194] trunk/src/dl-learner/org/dllearner

[<jen...@us...>]

Revision: 2194
          http://dl-learner.svn.sourceforge.net/dl-learner/?rev=2194&view=rev
Author:   jenslehmann
Date:     2010-07-09 20:00:32 +0000 (Fri, 09 Jul 2010)

Log Message:
-----------
script to generate a table of example accuracies

Modified Paths:
--------------
    trunk/src/dl-learner/org/dllearner/learningproblems/ClassLearningProblem.java
    trunk/src/dl-learner/org/dllearner/scripts/evaluation/HeuristicOverviewTableGenerator.java

Modified: trunk/src/dl-learner/org/dllearner/learningproblems/ClassLearningProblem.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/learningproblems/ClassLearningProblem.java	2010-07-09 12:22:02 UTC (rev 2193)
+++ trunk/src/dl-learner/org/dllearner/learningproblems/ClassLearningProblem.java	2010-07-09 20:00:32 UTC (rev 2194)
@@ -720,9 +720,11 @@
 	}
 	
 	// computes accuracy from coverage and protusion (changing this function may
-	// make it necessary to change the appoximation too)
-	private double getAccuracy(double coverage, double protusion) {
-		return (coverageFactor * coverage + Math.sqrt(protusion)) / (coverageFactor + 1);
+	// make it necessary to change the appoximation too) => not the case anymore
+	private double getAccuracy(double recall, double precision) {
+//		return (coverageFactor * coverage + Math.sqrt(protusion)) / (coverageFactor + 1);
+		// log: changed from precision^^0.5 (root) to precision^^0.8 as the root is too optimistic in some cases
+		return (coverageFactor * recall + Math.pow(precision, 0.8)) / (coverageFactor + 1);
 	}
 	
 	private double getFMeasure(double recall, double precision) {

Modified: trunk/src/dl-learner/org/dllearner/scripts/evaluation/HeuristicOverviewTableGenerator.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/evaluation/HeuristicOverviewTableGenerator.java	2010-07-09 12:22:02 UTC (rev 2193)
+++ trunk/src/dl-learner/org/dllearner/scripts/evaluation/HeuristicOverviewTableGenerator.java	2010-07-09 20:00:32 UTC (rev 2194)
@@ -19,6 +19,7 @@
  */
 package org.dllearner.scripts.evaluation;
 
+import java.text.DecimalFormat;
 import java.util.LinkedList;
 import java.util.List;
 
@@ -72,6 +73,7 @@
 	}
 	
 	private List<Input> inputs;
+	private DecimalFormat df = new DecimalFormat();
 	
 	public HeuristicOverviewTableGenerator(List<Input> inputs) {
 		this.inputs = inputs;
@@ -83,9 +85,18 @@
 			double recall = getRecall(input);
 			double fMeasureEq = getFMeasure(recall, precision, 1);
 			double fMeasureSc = getFMeasure(recall, precision, 3);
+			double aMeasureEq = getAMeasure(recall, precision, 1);
+			double aMeasureSc = getAMeasure(recall, precision, 3);
+			double predAccEq = getPredAcc(input, 1);
+			double predAccSc = getPredAcc(input, 3);
+			double jaccard = getJaccard(input);
 			
 			System.out.println("input: " + input);
-			System.out.println("FMeasure: eq. " + fMeasureEq + " sc. " + fMeasureSc);
+			System.out.println("recall: " + df.format(recall) + " precision: " + df.format(precision));
+			System.out.println("FMeasure: eq. " + df.format(fMeasureEq) + " sc. " + df.format(fMeasureSc));
+			System.out.println("AMeasure: eq. " + df.format(aMeasureEq) + " sc. " + df.format(aMeasureSc));
+			System.out.println("pred.acc.: eq. " + df.format(predAccEq) + " sc. " + df.format(predAccSc));
+			System.out.println("Jaccard: " + df.format(jaccard));
 			System.out.println();
 			
 		}
@@ -105,6 +116,24 @@
 					/ (Math.sqrt(factor) * precision + recall) ); 		
 	}
 	
+	private double getAMeasure(double recall, double precision, double factor) {
+		return (factor * recall + precision) / (factor + 1);
+	}
+	
+	@SuppressWarnings("unused")
+	private double getOwnMeasure(double recall, double precision, double factor) {
+//		return (factor * recall + Math.sqrt(precision)) / (factor + 1);
+		return (factor * recall + Math.pow(precision, 0.8)) / (factor + 1);
+	}
+	
+	private double getPredAcc(Input input, double factor) {
+		return (factor*input.intersectionSuggestionClass + input.kbInstances - input.classInstances - input.suggestionInstances + input.intersectionSuggestionClass) / (double) (input.kbInstances + (factor-1)*input.classInstances);
+	}
+	
+	private double getJaccard(Input input) {
+		return input.intersectionSuggestionClass / (double) (input.classInstances + input.suggestionInstances - input.intersectionSuggestionClass);
+	}
+	
 	/**
 	 * @param args none
 	 */


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