public INeuralNet Crossover(INeuralNet other)
{
if (other is OneLayerNeuralNet == false)
{
throw new ApplicationException("'other' should be of type COneLayerNeuralNet to be able to crossover with COneLayerNeuralNet.");
}
var child = new OneLayerNeuralNet(this.wages.GetLength(0), this.wages.GetLength(1));
child.wages = CrossoverHelper.Crossover(this.wages, (other as OneLayerNeuralNet).wages);
child.biasesInOutputLayer = CrossoverHelper.Crossover(this.biasesInOutputLayer, (other as OneLayerNeuralNet).biasesInOutputLayer);
return(child);
}
public INeuralNet Crossover(INeuralNet other)
{
if (other is MultiLayerNeuralNet == false)
{
throw new ApplicationException("'other' should be of type COneLayerNeuralNet to be able to crossover with COneLayerNeuralNet.");
}
var child = new MultiLayerNeuralNet(
this.wagesBetweenInputAndFirstHiddenLayer.GetLength(0),
this.wagesBetweenLastHiddenAndOutputLayer.GetLength(1),
this.wagesBetweenInputAndFirstHiddenLayer.GetLength(1),
this.wagesBetweenHiddenLayers.Length + 1);
var castedOther = other as MultiLayerNeuralNet;
child.wagesBetweenInputAndFirstHiddenLayer =
CrossoverHelper.Crossover(this.wagesBetweenInputAndFirstHiddenLayer, castedOther.wagesBetweenInputAndFirstHiddenLayer);
for (int i = 0; i < this.wagesBetweenHiddenLayers.Length; i++)
{
child.wagesBetweenHiddenLayers[i] =
CrossoverHelper.Crossover(this.wagesBetweenHiddenLayers[i], castedOther.wagesBetweenHiddenLayers[i]);
}
for (int i = 0; i < this.biasesInHiddenLayers.Length; i++)
{
child.biasesInHiddenLayers[i] =
CrossoverHelper.Crossover(this.biasesInHiddenLayers[i], castedOther.biasesInHiddenLayers[i]);
}
child.wagesBetweenLastHiddenAndOutputLayer =
CrossoverHelper.Crossover(this.wagesBetweenLastHiddenAndOutputLayer, castedOther.wagesBetweenLastHiddenAndOutputLayer);
child.biasesInOutputLayer =
CrossoverHelper.Crossover(this.biasesInOutputLayer, castedOther.biasesInOutputLayer);
return(child);
}