public void LearnNeverTest()
{
int[] layers = new int[] { 2,1 }; // no linear separity
MLPWatchdog nn = new WatchdogGenerator().Create(layers,1,new Sigmoid());
nn.LearnFactor=0.9;
nn.Momentum=0.5;
var response= nn.BPWatched(new BPWDRequest(XOR,10000,0,0.1,10));
Assert.AreEqual(response.Count,10);
Assert.AreEqual(response[9].Estimate,BPResponseEstimate.Failure);
}
public void LearnXORTest()
{
for(var x=0; x<5; x++) {
int[] layers = new int[] { 2,2,1 }; // linear separity
MLPWatchdog nn = new WatchdogGenerator().Create(layers,1,new Sigmoid());
nn.LearnFactor=0.9;
nn.Momentum=0.5;
var response= nn.BPWatched(new BPWDRequest(XOR,10000,0,0.001,10));
Assert.IsTrue(response.Count<10); // should learn faster
Assert.AreEqual(response.Last().Estimate,BPResponseEstimate.Success);
//sanity check
IsBetween(nn.Pulse(new double[] { 0,0 })[0],0,0.05);
IsBetween(nn.Pulse(new double[] { 0,1 })[0],0.95,1);
IsBetween(nn.Pulse(new double[] { 1,0 })[0],0.95,1);
IsBetween(nn.Pulse(new double[] { 1,1 })[0],0,0.05);
}
}
