/// <inheritdoc/>
public int Classify(double[] input)
{
if (input.Length > InputCount)
{
throw new AIFHError(
"Can't classify SOM with input size of " + InputCount
+ " with input data of count " + input.Length);
}
double minDist = double.PositiveInfinity;
int result = -1;
var rowWeights = _weights.ToRowArrays();
for (int i = 0; i < OutputCount; i++)
{
double dist = calcDist.Calculate(input, rowWeights[i]);
if (dist < minDist)
{
minDist = dist;
result = i;
}
}
return(result);
}
private void btnRecognize_Click(object sender, EventArgs e)
{
var ds = new DownSample(_entryImage);
_downsampled = ds.PerformDownSample(DownsampleWidth, DownsampleHeight);
sample.Invalidate();
int sampleSize = DownsampleHeight * DownsampleWidth;
char bestChar = '?';
double bestDistance = double.MaxValue;
foreach (char ch in _letterData.Keys)
{
double[] data = _letterData[ch];
double dist = _distCalc.Calculate(data, _downsampled);
if (dist < bestDistance)
{
bestDistance = dist;
bestChar = ch;
}
}
MessageBox.Show(@"That might be " + bestChar, @"Recognize");
ClearEntry();
}
/// <summary>
/// Find the nearest neighbor particle.
/// </summary>
/// <param name="target">The particle to look for neighbors to.</param>
/// <param name="particles">All particles.</param>
/// <param name="k">The number of particles to find.</param>
/// <param name="maxDist">The max distance to check.</param>
/// <returns>The nearest neighbors.</returns>
private IList <Particle> FindNearest(Particle target, IEnumerable <Particle> particles, int k, double maxDist)
{
IList <Particle> result = new List <Particle>();
var tempDist = new double[k];
int worstIndex = -1;
foreach (Particle particle in particles)
{
if (particle == target)
{
continue;
}
double d = _distanceCalc.Calculate(particle.Location, target.Location);
if (d > maxDist)
{
continue;
}
if (result.Count < k)
{
tempDist[result.Count] = d;
result.Add(particle);
worstIndex = MaxIndex(tempDist);
}
else if (d < tempDist[worstIndex])
{
tempDist[worstIndex] = d;
result[worstIndex] = particle;
worstIndex = MaxIndex(tempDist);
}
}
return(result);
}
/// <inheritdoc/>
public override double Evaluate()
{
double result = 0;
for (int i = 0; i < (_cities.Length - 1); i++)
{
// find current and next city
double[] city1 = _cities[_currentPath[i]];
double[] city2 = _cities[_currentPath[i + 1]];
result += _distance.Calculate(city1, city2);
}
return(result);
}
/// <summary>
/// Find the nearest cluster for an observation.
/// </summary>
/// <param name="observation">The observation.</param>
/// <returns>The nearest cluster.</returns>
public Cluster FindNearestCluster(double[] observation)
{
Cluster result = null;
double resultDist = double.PositiveInfinity;
foreach (Cluster cluster in _clusters)
{
double dist = _distanceMetric.Calculate(observation, cluster.Center);
if (dist < resultDist)
{
resultDist = dist;
result = cluster;
}
}
return(result);
}
public override double Evaluate()
{
return(_distance.Calculate(Ideal, _currentHolder));
}
