final List<BasicData> trainingData = ds.extractSupervised(0, 4, 4, 2);
final RBFNetwork network = new RBFNetwork(4, 4, 2);
network.reset(new MersenneTwisterGenerateRandom());
final ScoreFunction score = new ScoreRegressionData(trainingData);
final TrainNelderMead train = new TrainNelderMead(network, score);
performIterations(train, 1000, 0.01, true);
queryEquilateral(network, trainingData, species, 0, 1);
} catch (Throwable t) {