private RCConfiguration _GetELMConfigurationFromPSOParticle(Particula particle, DataProvider dProv)
{
int inputNodesLengh = particle.GetFlagCountFromSubListValues((int)dProv.InputsN);
if (inputNodesLengh == 0)
{
particle.PosicaoAtual[0] = 1;
inputNodesLengh = particle.GetFlagCountFromSubListValues((int)dProv.InputsN);
}
Data[] dataSet = new Data[dProv.DataSetLines];
int index = 0;
for (int i = 0; i < dProv.DataSetLines; i++)
{
index = 0;
dataSet[i] = new Data(new double[inputNodesLengh], new double[dProv.OutputsN]);
dataSet[i].Output = dProv.DataSet[i].Output;
for (int k = 0; k < dProv.InputsN; k++)
{
if (particle.PosicaoAtual[k] == 1)
{
dataSet[i].Input[index] = dProv.DataSet[i].Input[k];
index++;
}
}
}
DataProvider prov = new DataProvider(dataSet, EExecutionType.Predction, Util.Random);
int hiddenNodes = particle.GetHiddenNodes((int)dProv.InputsN, MaxHiddenNodes);
if (hiddenNodes == 0)
{
particle.PosicaoAtual[(int)dProv.InputsN] = 1;
hiddenNodes = particle.GetHiddenNodes((int)dProv.InputsN, MaxHiddenNodes);
}
prov.MaxClassificationClass = dProv.MaxClassificationClass;
return new RCConfiguration(prov, hiddenNodes, 1, 0.05, 1, EActivationFunctionType.SigmoidLogistic, EExecutionType.Predction);
}
private void _ELM(Particula p)
{
DataProvider prov = new DataProvider(_DataSetPath, EExecutionType.Predction, Util.Random);
RCConfiguration config = _GetELMConfigurationFromPSOParticle(p, prov);
config.Prov.MaxValue = prov.MaxValue.Clone() as double[];
config.Prov.MinValue = prov.MinValue.Clone() as double[];
config.Prov.NormalizeData(inputA, inputB, outputA, outputB);
config.Prov.ShuffleDataSet(1);
config.Prov.SplitData();
RC elm = new RC(config.Prov.TrainSet, config.Prov.ValidationSet, config);
try
{
elm.Run();
}
catch
{ }
RCEvaluator eval = new RCEvaluator(elm, EEvaluationInfo.EMQ | EEvaluationInfo.DEV | EEvaluationInfo.EPMA);
eval.Evaluate();
double fitness = eval.TrainEPMA + (2 * eval.ValidationDEV * p.GetFlagCountFromSubListValues((int)config.Prov.InputsN) / config.Prov.ValidationSetLines) + (config.HidenNodesNumber / MaxHiddenNodes);
p.Eval = eval;
p.Fitness = fitness;
p.Config = config;
count++;
// Variação de C1 e C2
if (_VariarC1C2)
{
if (count % _LimiteVariacaoC1C2 == 0)
{
_C1 = _C1 - _TaxaVariacaoC1C2;
_C2 = _C2 + _TaxaVariacaoC1C2;
}
}
// Variação de W
if (_VariarW)
{
if (count % _LimiteVariacaoW == 0)
_W = _W - _TaxaVariacaoW;
}
}
