public void TrainDataSet()
{
do
{
_iterations++; _error = 0.0;
_idx.Permute(DataSet.Size);
for (int i = 0; i < DataSet.Size; i++)
{
var input = DataSet.Data[_idx[i]].Input;
var output = DataSet.Data[_idx[i]].Output;
_error += Network.Train(ref input,
ref output,
TrainingRate, Momentum);
DataSet.Data[_idx[i]].Input = input;
DataSet.Data[_idx[i]].Output = output;
}
_errorHistory.Add(_error);
if (_iterations % NudgeWindow == 0)
{
CheckNudge();
}
IterationCompleted?.Invoke(this, new TrainingProgressReport(_iterations, _error));
} while (_error > MaxError && _iterations < MaxIterations);
}
public void CheckingPermutation()
{
var list = new List <int>()
{
1, 2, 3, 4, 5
};
var result = Permutator.Permute(list);
Assert.True(result.Count == 120);
}
public void CanPermute()
{
string str = "ABC";
int n = str.Length;
var result = Permutator.Permute(str);
Assert.Equal(result, new[] {
"ABC",
"ACB",
"BAC",
"BCA",
"CBA",
"CAB"
});
}
public int FindShortestDistance(bool includePathBack)
{
var pathFinder = new PathFinder();
var points = FindAllPoints();
var permutatios = Permutator.Permute(points.Keys.ToArray());
permutatios = permutatios.Where(p => p[0] == '0');
// Remembering all the distances speed things up a bit...
var knownDistances = new Dictionary <string, int>();
var shortest = int.MaxValue;
foreach (var permutation in permutatios)
{
var sum = 0;
char[] currentPermutation = permutation;
if (includePathBack)
{
currentPermutation = permutation.Concat(new[] { '0' }).ToArray();
}
for (int i = 0; i < currentPermutation.Length - 1; i++)
{
var key = "" + currentPermutation[i] + currentPermutation[i + 1];
if (!knownDistances.ContainsKey(key))
{
knownDistances.Add(key, pathFinder.FindShortestPath(
points[currentPermutation[i]],
points[currentPermutation[i + 1]],
NodeTypeAtPos));
}
sum += knownDistances[key];
}
shortest = Math.Min(shortest, sum);
}
return(shortest);
}
