public GradientDescent()
{
// NOTE: Newest training set at index 0
_trainingSets = new TrainingSet[Constants.MaxNumberOfTrainingSets];
_hypothesis = new Hypothesis(new Parameters(0f, 0f));
for (int i = 0; i < Constants.MaxNumberOfTrainingSets; i++)
{
_trainingSets[i] = new TrainingSet(0f, 0f);
}
}
public GradientDescent(int numberOfTrainingSetsUsedForGD, int numberOfUpdateCycles, float alpha)
{
// NOTE: Newest training set at index 0
_trainingSets = new TrainingSet[Constants.MaxNumberOfTrainingSets];
_hypothesis = new Hypothesis(new Parameters(0f, 0f), numberOfTrainingSetsUsedForGD, alpha);
_numberOfTrainingSetsUsedForGD = numberOfTrainingSetsUsedForGD;
_numberOfUpdateCycles = numberOfUpdateCycles;
for (int i = 0; i < Constants.MaxNumberOfTrainingSets; i++)
{
_trainingSets[i] = new TrainingSet(0f, 0f);
}
}
