@Override public Double[] call() throws Exception { Double[] r = new Double[2]; double e = theEvaluator.evaluateSubset(tempCopy); r[0] = new Double(attBeingEvaluated); r[1] = e; return r; } });
@Override public Double[] call() throws Exception { Double[] r = new Double[2]; double e = theEvaluator.evaluateSubset(tempCopy); r[0] = new Double(attBeingEvaluated); r[1] = e; return r; } });
if (k != data.classIndex()) { group.set(k); merit[k] -= evaluator.evaluateSubset(group); m_evalsTotal++; group.clear(k);
best_merit = ((SubsetEvaluator) eval).evaluateSubset(best_group); temp_merit = ((SubsetEvaluator) eval).evaluateSubset(temp_group);
m_numAttribs = data.numAttributes(); best_merit = ASEvaluator.evaluateSubset(m_bestGroup); m_evaluations++; sizeOfBest = countFeatures(m_bestGroup); tempMerit = ASEvaluator.evaluateSubset(tempGroup); tempMerit = ASEvaluator.evaluateSubset(tempGroup); m_evaluations++; if (tempMerit >= best_merit) {
best_merit = ASEvaluator.evaluateSubset(m_best_group); temp_merit = ASEvaluator.evaluateSubset(temp_group); if (m_backward) { z = (temp_merit >= temp_best);
best_merit = ASEvaluator.evaluateSubset(m_best_group); temp_merit = ASEvaluator.evaluateSubset(temp_group); if (m_backward) { z = (temp_merit >= temp_best);
/** * evaluates an entire population. Population members are looked up in a hash * table and if they are not found then they are evaluated using ASEvaluator. * * @param ASEvaluator the subset evaluator to use for evaluating population * members * @throws Exception if something goes wrong during evaluation */ private void evaluatePopulation(SubsetEvaluator ASEvaluator) throws Exception { int i; double merit; for (i = 0; i < m_popSize; i++) { // if its not in the lookup table then evaluate and insert if (m_lookupTable.containsKey(m_population[i].getChromosome()) == false) { merit = ASEvaluator.evaluateSubset(m_population[i].getChromosome()); m_population[i].setObjective(merit); m_lookupTable.put(m_population[i].getChromosome(), m_population[i]); } else { GABitSet temp = m_lookupTable.get(m_population[i].getChromosome()); m_population[i].setObjective(temp.getObjective()); } } }
best_merit = ASEvaluator.evaluateSubset(m_bestGroup); sizeOfBest = countFeatures(m_bestGroup); } else { best_merit = ASEvaluator.evaluateSubset(m_bestGroup); tempSize = countFeatures(temp); if (tempSize <= sizeOfBest) { tempMerit = ASEvaluator.evaluateSubset(temp); if (tempMerit >= best_merit) { sizeOfBest = tempSize; tempMerit = ASEvaluator.evaluateSubset(temp); if (tempMerit > best_merit) { m_bestGroup = temp;
bestMerit = evaluator.evaluateSubset(bestGroup); tempMerit = evaluator.evaluateSubset(tempGroup);
best_merit = ASEvaluator.evaluateSubset(best_group); merit = ASEvaluator.evaluateSubset(temp_group); m_totalEvals++;
best_merit = ASEvaluator.evaluateSubset(best_group); merit = ASEvaluator.evaluateSubset(temp_group); m_totalEvals++;
bestMerit = evaluator.evaluateSubset(bestGroup); tempMerit = evaluator.evaluateSubset(tempGroup);
temp_merit = ((SubsetEvaluator) m_SubsetEval).evaluateSubset(temp_group);
} else { m_setSizeEval.buildEvaluator(testData[f]); testMerit[f][s] = ((SubsetEvaluator)m_setSizeEval).evaluateSubset(searchResults[f].getBestGroupOfSize( s));