public void InitializeService(NetworkInitializer initializer)
{
LVQInitializer input = (LVQInitializer)initializer;
int VEC_LEN = input.patterns[0].Length;
int TRAINING_PATTERNS = input.patterns.GetUpperBound(0) + 1;
inputs = new double[TRAINING_PATTERNS][];
for (int i = 0; i < TRAINING_PATTERNS; i++)
{
inputs[i] = new double[VEC_LEN];
}
for (int i = 0; i < TRAINING_PATTERNS; i++)
{
for (int j = 0; j < VEC_LEN; j++)
{
inputs[i][j] = input.patterns[i][j];
}
}
this.clusters = new int[TRAINING_PATTERNS];
int[] formedAnswers = Normalize.FormAnswersLVQ(input.answers);
for (int i = 0; i < TRAINING_PATTERNS; i++)
{
this.clusters[i] = formedAnswers[i];
}
this.minError = input.minError;
this.learningRate = input.learningRate;
this.decayRate = input.decayRate;
this.numOfClusters = input.numOfClusters;
}
public virtual void InitializeService(NetworkInitializer initializer)
{
BPNInitializer input = (BPNInitializer)initializer;
this.parameters = input.parameters;
this.hidden = input.hidden;
this.learningRate = input.learningRate;
this.Momentum = input.Momentum;
this.minError = input.minError;
layerSizes = new int[3] {
this.parameters, this.hidden, 1
};
TFuncs = new TransferFunction[3] {
TransferFunction.None,
TransferFunction.BipolarSigmoid,
TransferFunction.BipolarSigmoid
};
}
