public void ApplyWeightAdjustments_UpdatesWeight()
{
//// SETUP
const double InitialWeight = 0.25d;
const double FireInput = 1.234d;
const double ErrorSignal1A = -2.3d;
const double ErrorSignal1B = -9.87d;
const double AccumulatedError1 = ErrorSignal1A + ErrorSignal1B;
const double ErrorSignal2 = 3.2345d;
const float Momentum = 0.9f;
const float LearningRate = 0.1f;
const double ExpectedWeight1 = (AccumulatedError1 * FireInput * LearningRate) + InitialWeight;
const double ExpectedWeight2 = ExpectedWeight1 + (ErrorSignal2 * FireInput * LearningRate) + (Momentum * (AccumulatedError1 * FireInput * LearningRate));
var mockTarget = new Mock<ISupervisedLearnerNode>();
var mockSource = new Mock<ISupervisedLearnerNode>();
// Create the test object.
var connection = new BackpropagationConnection(InitialWeight, mockSource.Object, mockTarget.Object);
connection.Fire(FireInput);
// EXECUTION
connection.ReportError(ErrorSignal1A);
connection.ReportError(ErrorSignal1B);
connection.ApplyWeightAdjustments(LearningRate, Momentum);
var actual1 = connection.Weight;
connection.ClearCachedErrors();
connection.ReportError(ErrorSignal2);
connection.ApplyWeightAdjustments(LearningRate, Momentum);
var actual2 = connection.Weight;
// VERIFICATION
Assert.AreEqual(ExpectedWeight1, actual1, Epsilon);
Assert.AreEqual(ExpectedWeight2, actual2, Epsilon);
}
public void ClearCachedErrors_PropogatesThroughNetwork()
{
//// SETUP
const double InitialWeight = 0.25d;
var mockTarget = new Mock<ISupervisedLearnerNode>();
var mockSource = new Mock<ISupervisedLearnerNode>();
// Create the test object.
var connection = new BackpropagationConnection(InitialWeight, mockSource.Object, mockTarget.Object);
// EXECUTION
connection.ClearCachedErrors();
// VERIFICATION
mockTarget.Verify(mock => mock.ClearCachedErrors(), Times.Once());
}