public void crossover() {
int j, countCross = 0;
Sampling samp = new Sampling(popSize);
int p1 = -1;
for (j = 0; j < popSize; j++) {
if (Randomize.Rand() < Parameters.crossoverProbability) {
if (p1 == -1) {
p1 = samp.getSample();
} else {
int p2 = samp.getSample();
crossTwoParents(p1, p2, countCross, countCross + 1);
countCross += 2;
p1 = -1;
}
} else {
crossOneParent(samp.getSample(), countCross++);
}
}
if (p1 != -1) {
crossOneParent(p1, countCross++);
}
}
public void TournamentSelectionWOR() {
int i, j, winner, candidate;
Sampling samp = new Sampling(popSize);
for (i = 0; i < popSize; i++) {
// There can be only one
winner = samp.getSample();
for (j = 1; j < tournamentSize; j++) {
candidate = samp.getSample();
if (population[candidate].compareToIndividual(
population[winner], Parameters.optimizationMethod)
> 0) {
winner = candidate;
}
}
offspringPopulation[i] = cf.cloneClassifier(population[winner]);
}
}