@Override
public double[] fitness(Node individual) {
DataSet dataSetView = this.context.getCurrentDataSet();
TreeEvaluator evaluator = context.getConfiguration().getEvaluator();
double[] fitness = new double[3];
double fitnessLenght;
List<Bounds[]> evaluate;
try {
evaluate = evaluator.evaluate(individual, context);
StringBuilder builder = new StringBuilder();
individual.describe(builder);
fitnessLenght = builder.length();
} catch (TreeEvaluationException ex) {
Logger.getLogger(CharmaskMatchLengthObjective.class.getName()).log(Level.SEVERE, null, ex);
Arrays.fill(fitness, Double.POSITIVE_INFINITY);
return fitness;
}
//Calculates the true positive and false positive matches:
//match stats makes sense only for tp e fp values... we cannot use instance statistic formulas other than precision
BasicStats statsOverall = new BasicStats();
//char stats can be managed as ususal
BasicStats statsCharsOverall = new BasicStats();
int i = 0;
for (Bounds[] result : evaluate) {
BasicStats stats = new BasicStats();
BasicStats statsChars = new BasicStats();
//Characted extracted in the right place (match)
Example example = dataSetView.getExample(i);
List<Bounds> expectedMatchMask = example.getMatch();
List<Bounds> expectedUnmatchMask = example.getUnmatch();
List<Bounds> annotatedMask = new FastList(expectedMatchMask);
annotatedMask.addAll(expectedUnmatchMask);
stats.tp = countIdenticalRanges(result, expectedMatchMask);
stats.fp = Bounds.countRangesThatCollideZone(result, annotatedMask) - stats.tp;
statsChars.tp = intersection(result, expectedMatchMask);
statsChars.fp = intersection(result, expectedUnmatchMask);
statsOverall.add(stats);
statsCharsOverall.add(statsChars);
i++;
}
statsCharsOverall.tn = dataSetView.getNumberUnmatchedChars() - statsCharsOverall.fp;
statsCharsOverall.fn = dataSetView.getNumberMatchedChars() - statsCharsOverall.tp;
fitness[0] = (statsCharsOverall.fpr() + statsCharsOverall.fnr()) * 100.0;
fitness[1] = Math.abs(statsOverall.fp + statsOverall.tp - dataSetView.getNumberMatches()); // ABS((TP+FP) - (TP+FN)) alias ABS(Number_Extractions - Number_Matches))
fitness[2] = fitnessLenght;
return fitness;
}
@Override
public TreeEvaluator getTreeEvaluator() {
return context.getConfiguration().getEvaluator();
}