private InferenceLayer <LinearMembershipFunction> Create()
{
var lrate = 1e-2;
var smoothingAvarageRate = 1e-3;
var ruleset = new FirstLevelRuleset(5e-1);
var termLayer1 = new TermLayer <LinearMembershipFunction>(learningRate: lrate,
smoothingAverageRate: smoothingAvarageRate,
termsLimit: 8, competitionLooseLimit: 500);
var termLayer2 = new TermLayer <LinearMembershipFunction>(learningRate: lrate,
smoothingAverageRate: smoothingAvarageRate,
termsLimit: 12, competitionLooseLimit: 500);
var termLayer3 = new TermLayer <LinearMembershipFunction>(learningRate: lrate,
smoothingAverageRate: smoothingAvarageRate,
termsLimit: 18, competitionLooseLimit: 500);
var termLayer4 = new TermLayer <LinearMembershipFunction>(learningRate: lrate,
smoothingAverageRate: smoothingAvarageRate,
termsLimit: 30, competitionLooseLimit: 500);
var fis = new InferenceLayer <LinearMembershipFunction>(
new[] { termLayer1, termLayer2, termLayer3, termLayer4 },
ruleset, smoothingAvarageRate);
return(fis);
}
public void CreationStep_InitialInfinities(double input)
{
var layers = new TermLayer <LinearMembershipFunction>();
layers.CreationStep(input, 0, 0);
Assert.AreEqual(3, layers.Cores.Length);
Assert.IsTrue(layers.Cores.Any(z => Math.Abs(z.X - input) < 1e-5));
}
private InferenceLayer <PiMembershipFunction> Create()
{
var lrate = 1e-3;
var smoothingAvarageRate = 1e-3;
var ruleset = new FirstLevelRuleset(2e-1);
var termLayer = new TermLayer <PiMembershipFunction>(learningRate: lrate,
smoothingAverageRate: smoothingAvarageRate,
termsLimit: 200, competitionLooseLimit: 100); //TermCore.Create(0), TermCore.Create(1)
var fis = new InferenceLayer <PiMembershipFunction>(new[] { termLayer }, ruleset, smoothingAvarageRate);
return(fis);
}
public void CreationStep_CorrectlyOutsideTerm(double input)
{
var zero = TermCore.Create(0);
var one = TermCore.Create(1);
zero.AccumulatedError = 1;
one.AccumulatedError = 1;
var layers = new TermLayer <LinearMembershipFunction>(new[]
{
zero, one
});
layers.CreationStep(input, 0, 0);
Assert.AreEqual(5, layers.Cores.Length);
Assert.IsTrue(layers.Cores.Any(z => Math.Abs(z.X - input) < 1e-5));
}
public void CreationStep_CorrectlyCreatedMidleTerm(double input)
{
var zero = TermCore.Create(0);
var one = TermCore.Create(1);
zero.AccumulatedError = 1;
one.AccumulatedError = 1;
var layers = new TermLayer <LinearMembershipFunction>(new[]
{
zero, one
});
layers.CreationStep(input, 0, 0);
Assert.AreEqual(5, layers.Cores.Length);
Assert.AreEqual(input, layers.Cores[2].X);
}
public void BackpropError_AccumulatedErrorComputedCorrectly()
{
var zero = TermCore.Create(0);
var one = TermCore.Create(1);
var layers = new TermLayer <LinearMembershipFunction>(new[]
{
zero, one
}, learningRate: 1e-1, smoothingAverageRate: 1e-1);
for (var i = 0; i < 100; i++)
{
layers.BackpropError(0, 5);
layers.BackpropError(1, -3);
}
Assert.AreEqual(5, zero.AccumulatedError, 1e-2);
Assert.AreEqual(-3, one.AccumulatedError, 1e-2);
}
public void BackpropError_CoresLearnedCorrectly(double initialZero, double initialOne)
{
var zero = TermCore.Create(initialZero);
var one = TermCore.Create(initialOne);
var layers = new TermLayer <LinearMembershipFunction>(new[]
{
zero, one
}, learningRate: 1e-1);
for (var i = 0; i < 100; i++)
{
layers.BackpropError(0, -zero.X);
layers.BackpropError(1, 1.0 - one.X);
}
Assert.AreEqual(0, zero.X, 1e-2);
Assert.AreEqual(1, one.X, 1e-2);
}
