public void Train_IfTrainingSetDoesNotMatchNetwork_Throw()
{
var trainer = GetSampleTrainer();
var trainingSet = GetTrainingSet();
var nn = new TwoLayerPerceptron(3, 1, 1);
Assert.Throws<NeuralNetworkException>(() => trainer.Train(trainingSet, nn));
}
public INeuralNetwork GetSampleNN()
{
var nn = new TwoLayerPerceptron(2, 1, 1);
nn.Weights[0] = new[] { 1.0, 2.0, 3.0 };
nn.Weights[1] = new[] { 1.5, 0.5 };
return(nn);
}
public void Train_IfTrainingSetDoesNotMatchNetwork_Throw()
{
var trainer = GetSampleTrainer();
var trainingSet = GetTrainingSet();
var nn = new TwoLayerPerceptron(3, 1, 1);
Assert.Throws <NeuralNetworkException>(() => trainer.Train(trainingSet, nn));
}
public void ConstructorShouldCreateCorrectArrays()
{
var nn = new TwoLayerPerceptron(1, 2, 4);
Assert.Equal(1, nn.NumInputs);
Assert.Equal(2, nn.NumHidden);
Assert.Equal(4, nn.NumOutputs);
Assert.Equal(4, nn.HiddenWeights.Length);
Assert.Equal(12, nn.OutputWeights.Length);
}
public void ConstructorShouldCreateCorrectArrays()
{
var nn = new TwoLayerPerceptron(1, 2, 4);
Assert.Equal(1, nn.NumInputs);
Assert.Equal(2, nn.NumHidden);
Assert.Equal(4, nn.NumOutputs);
Assert.Equal(4, nn.HiddenWeights.Length);
Assert.Equal(12, nn.OutputWeights.Length);
}
private static TwoLayerPerceptron GetNeuralNetwork()
{
// Setup generated from NeuralNetworksTests.xlsx in this folder.
var nn = new TwoLayerPerceptron(4, 6, 3);
nn.HiddenWeights[0] = 0.1; nn.HiddenWeights[1] = 0.2; nn.HiddenWeights[2] = 0.3; nn.HiddenWeights[3] = 0.4; nn.HiddenWeights[4] = 0.5;
nn.HiddenWeights[5] = 0.11; nn.HiddenWeights[6] = 0.21; nn.HiddenWeights[7] = 0.31; nn.HiddenWeights[8] = 0.41; nn.HiddenWeights[9] = 0.51;
nn.HiddenWeights[10] = 0.12; nn.HiddenWeights[11] = 0.22; nn.HiddenWeights[12] = 0.32; nn.HiddenWeights[13] = 0.42; nn.HiddenWeights[14] = 0.52;
nn.HiddenWeights[15] = 0.13; nn.HiddenWeights[16] = 0.23; nn.HiddenWeights[17] = 0.33; nn.HiddenWeights[18] = 0.43; nn.HiddenWeights[19] = 0.53;
nn.HiddenWeights[20] = 0.14; nn.HiddenWeights[21] = 0.24; nn.HiddenWeights[22] = 0.34; nn.HiddenWeights[23] = 0.44; nn.HiddenWeights[24] = 0.54;
nn.HiddenWeights[25] = 0.15; nn.HiddenWeights[26] = 0.25; nn.HiddenWeights[27] = 0.35; nn.HiddenWeights[28] = 0.45; nn.HiddenWeights[29] = 0.55;
nn.OutputWeights[0] = 1.1; nn.OutputWeights[1] = 1.11; nn.OutputWeights[2] = 1.12; nn.OutputWeights[3] = 1.13; nn.OutputWeights[4] = 1.14; nn.OutputWeights[5] = 1.15; nn.OutputWeights[6] = 1.16;
nn.OutputWeights[7] = 1.2; nn.OutputWeights[8] = 1.21; nn.OutputWeights[9] = 1.22; nn.OutputWeights[10] = 1.23; nn.OutputWeights[11] = 1.24; nn.OutputWeights[12] = 1.25; nn.OutputWeights[13] = 1.26;
nn.OutputWeights[14] = 1.3; nn.OutputWeights[15] = 1.31; nn.OutputWeights[16] = 1.32; nn.OutputWeights[17] = 1.33; nn.OutputWeights[18] = 1.34; nn.OutputWeights[19] = 1.35; nn.OutputWeights[20] = 1.36;
return(nn);
}
private static TwoLayerPerceptron GetNeuralNetwork()
{
// Setup generated from NeuralNetworksTests.xlsx in this folder.
var nn = new TwoLayerPerceptron(4, 6, 3);
nn.HiddenWeights[0] = 0.1; nn.HiddenWeights[1] = 0.2; nn.HiddenWeights[2] = 0.3; nn.HiddenWeights[3] = 0.4; nn.HiddenWeights[4] = 0.5;
nn.HiddenWeights[5] = 0.11; nn.HiddenWeights[6] = 0.21; nn.HiddenWeights[7] = 0.31; nn.HiddenWeights[8] = 0.41; nn.HiddenWeights[9] = 0.51;
nn.HiddenWeights[10] = 0.12; nn.HiddenWeights[11] = 0.22; nn.HiddenWeights[12] = 0.32; nn.HiddenWeights[13] = 0.42; nn.HiddenWeights[14] = 0.52;
nn.HiddenWeights[15] = 0.13; nn.HiddenWeights[16] = 0.23; nn.HiddenWeights[17] = 0.33; nn.HiddenWeights[18] = 0.43; nn.HiddenWeights[19] = 0.53;
nn.HiddenWeights[20] = 0.14; nn.HiddenWeights[21] = 0.24; nn.HiddenWeights[22] = 0.34; nn.HiddenWeights[23] = 0.44; nn.HiddenWeights[24] = 0.54;
nn.HiddenWeights[25] = 0.15; nn.HiddenWeights[26] = 0.25; nn.HiddenWeights[27] = 0.35; nn.HiddenWeights[28] = 0.45; nn.HiddenWeights[29] = 0.55;
nn.OutputWeights[0] = 1.1; nn.OutputWeights[1] = 1.11; nn.OutputWeights[2] = 1.12; nn.OutputWeights[3] = 1.13; nn.OutputWeights[4] = 1.14; nn.OutputWeights[5] = 1.15; nn.OutputWeights[6] = 1.16;
nn.OutputWeights[7] = 1.2; nn.OutputWeights[8] = 1.21; nn.OutputWeights[9] = 1.22; nn.OutputWeights[10] = 1.23; nn.OutputWeights[11] = 1.24; nn.OutputWeights[12] = 1.25; nn.OutputWeights[13] = 1.26;
nn.OutputWeights[14] = 1.3; nn.OutputWeights[15] = 1.31; nn.OutputWeights[16] = 1.32; nn.OutputWeights[17] = 1.33; nn.OutputWeights[18] = 1.34; nn.OutputWeights[19] = 1.35; nn.OutputWeights[20] = 1.36;
return nn;
}
public INeuralNetwork GetSampleNN()
{
var nn = new TwoLayerPerceptron(2, 1, 1);
nn.Weights[0] = new[] {1.0, 2.0, 3.0};
nn.Weights[1] = new[] {1.5, 0.5};
return nn;
}
