public void XOR(int iterations, double minimumAccuracy)
{
var mlp = new MultilayerPerceptron <Tanh>(2, new int[] { 10, 10 }, 1);
double[][] inputs = new double[][] {
new double[] { 0, 0 },
new double[] { 1, 0 },
new double[] { 0, 1 },
new double[] { 1, 1 },
};
double[][] outputs = new double[][] {
new double[] { 0 },
new double[] { 1 },
new double[] { 1 },
new double[] { 0 },
};
double[] output = new double[1];
for (int i = 0; i < iterations; i++)
{
for (int j = 0; j < inputs.Length; j++)
{
mlp.Predict(inputs[j], output);
mlp.Train(outputs[j], 0.4, 0.9);
}
}
for (int j = 0; j < inputs.Length; j++)
{
mlp.Predict(inputs[j], output);
double diff = 1 - Math.Abs(output[0] - outputs[j][0]);
Assert.GreaterOrEqual(diff, minimumAccuracy);
}
}
public void Iris(int iterations, double minimumAccuracy)
{
string[] lines = File.ReadAllLines("./Data/iris.csv");
double[][] inputs = new double[lines.Length][];
double[][] outputs = new double[lines.Length][];
for (int i = 0; i < lines.Length; i++)
{
inputs[i] = new double[4];
outputs[i] = new double[1];
string[] values = lines[i].Split(',');
for (int j = 0; j < 4; j++)
{
inputs[i][j] = double.Parse(values[j]);
}
outputs[i][0] = Map(values[4]);
}
for (int i = 0; i < 4; i++)
{
double min = double.PositiveInfinity;
double max = double.NegativeInfinity;
for (int j = 0; j < inputs.Length; j++)
{
if (inputs[j][i] < min)
{
min = inputs[j][i];
}
if (inputs[j][i] > max)
{
max = inputs[j][i];
}
}
for (int j = 0; j < inputs.Length; j++)
{
inputs[j][i] = Normalize((inputs[j][i] - min) / (max - min));
}
}
var mlp = new MultilayerPerceptron <Tanh>(4, new int[] { 10, 10 }, 1);
double normalizedCorrect = 0;
double[] output = new double[1];
for (int i = 0; i < iterations; i++)
{
int correct = 0;
for (int j = 0; j < inputs.Length; j++)
{
mlp.Predict(inputs[j], output);
mlp.Train(outputs[j], 0.1, 0.4);
double expectedOutput = outputs[j][0];
if (Map(expectedOutput) == Map(output[0]))
{
correct++;
}
}
normalizedCorrect = (double)correct / inputs.Length;
}
Assert.GreaterOrEqual(normalizedCorrect, minimumAccuracy);
}