//private Vector lastWeights;
//public Vector LastWeights
//{
// get
// {
// return lastWeights;
// }
//}
/// <summary>
/// Tworzy nowy perceptron na podstawie zadanego wektora wag
/// </summary>
public Perceptron(Vector weightVector)
{
if (weightVector == null)
{
throw new NullReferenceException("Przekazany wektor wag jest niezainicjowany");
}
weights = weightVector;
outputFunctionDelegate = biasFunction;
}
/// <summary>
/// Konstruktor
/// Tworzy wektor wag na podstawie wartości losowych 0.0 - 1.0
/// </summary>
public Perceptron(int dimension, int seed = 0)
{
weights = new Vector(dimension);
Random r = seed == 0 ? new Random() : new Random(seed);
for (int i = 0; i < weights.Dimension; i++)
{
weights[i] = r.NextDouble();
}
outputFunctionDelegate = biasFunction;
//weights.round();
//lastWeights = weights;
}
/// <summary>
/// Funkcja przeznaczona do zmiany typu funkcji wyjścia perceptronu
/// </summary>
public void setOutputFunctionType(PerceptronOutputFunctionType type)
{
switch (type)
{
case PerceptronOutputFunctionType.BiasFunction:
{
outputFunctionDelegate = biasFunction;
} break;
case PerceptronOutputFunctionType.SigmoidalFunction:
{
outputFunctionDelegate = sigmoidalFunction;
} break;
}
}
