public static void MInitializeCentersRandomlyBetweenMaxMinRanges(List <MyPoint> aoPList, ref List <ClusterCenterPoint> aoCList, int aiNumClusters)
{
ClusterCenterPoint koCP;
int kiNum;
// determine ranges
double kdMinX = (from koP in aoPList select koP.VdX).Min( );
double kdMinY = (from koP in aoPList select koP.VdY).Min( );
double kdMaxX = (from koP in aoPList select koP.VdX).Max( );
double kdMaxY = (from koP in aoPList select koP.VdX).Max( );
// initialize cluster centers randomly
Random koRand = new Random(( int )DateTime.Now.Ticks);
aoCList = new List <ClusterCenterPoint>( );
for (int i = 0; i < aiNumClusters; i++)
{
//ClusterCenterPoint cp = new ClusterCenterPoint { Cx = rand.NextDouble() * (maxX - minX), Cy = rand.NextDouble() * (maxY - minY) };
kiNum = ( int )koRand.NextDouble( ) * aoPList.Count;
koCP = new ClusterCenterPoint {
VdCx = aoPList[kiNum].VdX, VdCy = aoPList[kiNum].VdY
};
koCP.ViClusterID = i;
aoCList.Add(koCP);
}
}
public static void MInitializeCentersRandomlyFromGivenPoints(List <MyPoint> aoPList, ref List <ClusterCenterPoint> aoCList, int aiNumClusters)
{
ClusterCenterPoint koCP;
Random koRand = new Random(( int )DateTime.Now.Ticks);
List <int> koPListInt = new List <int>( );
int kiNum;
aoCList = new List <ClusterCenterPoint>( );
for (int i = 0; i < aoPList.Count; i++)
{
koPListInt.Add(i);
}
for (int i = 0; i < aiNumClusters; i++)
{
kiNum = koRand.Next(koPListInt.Count);
koCP = new ClusterCenterPoint {
VdCx = aoPList[kiNum].VdX, VdCy = aoPList[kiNum].VdY
};
koCP.ViClusterID = i;
koPListInt.RemoveAt(kiNum); // remove the number that has been selected so that it does not get selected again
aoCList.Add(koCP);
}
if (aoCList.Count < aiNumClusters)
{
throw new Exception("problem in initializing cluster centers..");
}
}
public static void InitializeCentersRandomlyFromGivenPoints(List <MyPoint> PList, ref List <ClusterCenterPoint> CList, int numClusters)
{
Random rand = new Random((int)DateTime.Now.Ticks);
CList = new List <ClusterCenterPoint>();
List <int> PListInt = new List <int>();
for (int i = 0; i < PList.Count; i++)
{
PListInt.Add(i);
}
for (int i = 0; i < numClusters; i++)
{
int num = rand.Next(PListInt.Count);
ClusterCenterPoint cp = new ClusterCenterPoint
{
Cx = PList[num].X,
Cy = PList[num].Y
};
cp.ClusterID = i;
PListInt.RemoveAt(num); // remove the number that has been selected so that it does not get selected again
CList.Add(cp);
}
if (CList.Count < numClusters)
{
throw new Exception("problem in initializing cluster centers..");
}
}
public static void InitializeCentersRandomlyBetweenMaxMinRanges(List <MyPoint> PList, ref List <ClusterCenterPoint> CList, int numClusters)
{
// determine ranges
double minX = (from p in PList select p.X).Min();
double minY = (from p in PList select p.Y).Min();
double maxX = (from p in PList select p.X).Max();
double maxY = (from p in PList select p.X).Max();
// initialize cluster centers randomly
Random rand = new Random((int)DateTime.Now.Ticks);
CList = new List <ClusterCenterPoint>();
for (int i = 0; i < numClusters; i++)
{
//ClusterCenterPoint cp = new ClusterCenterPoint { Cx = rand.NextDouble()*(maxX - minX), Cy = rand.NextDouble() * (maxY - minY) };
int num = (int)rand.NextDouble() * PList.Count;
ClusterCenterPoint cp = new ClusterCenterPoint {
Cx = PList[num].X, Cy = PList[num].Y
};
cp.ClusterID = i;
CList.Add(cp);
}
}
public static void MInitializeCentersRandomlyFromKPP(List <MyPoint> aoPList, ref List <ClusterCenterPoint> aoCList, int aiNumClusters)
{
Random koRand = new Random(( int )DateTime.Now.Ticks);
List <int> koPListInt = new List <int>( );
int kiNum;
double kdRandom;
double kdSumProbab;
double kdDist;
double kdDistPrev;
double kdDxSquared;
double[] kdDxPrimeSquared;
ClusterCenterPoint koCP;
aoCList = new List <ClusterCenterPoint>( );
for (int i = 0; i < aoPList.Count; i++)
{
koPListInt.Add(i);
}
//step1: of KPP - choose a center randomly from given set of points
kiNum = koRand.Next(koPListInt.Count);
koCP = new ClusterCenterPoint {
VdCx = aoPList[kiNum].VdX, VdCy = aoPList[kiNum].VdY
};
koCP.ViClusterID = 0;
koPListInt.RemoveAt(kiNum); // remove the number that has been selected so that it does not get selected again
aoCList.Add(koCP);
for (int i = 1; i < aiNumClusters; i++)
{ // Step2: Compute D(x)^2 where D(x) is the distance of x from closest centers chosen.
kdDxSquared = 0;
kdDxPrimeSquared = new double[koPListInt.Count];
for (int m = 0; m < koPListInt.Count; m++)
{
kdDistPrev = double.MaxValue;
foreach (ClusterCenterPoint koCCP in aoCList)
{
kdDist = MFindDistance(aoPList[koPListInt[m]].VdX, aoPList[koPListInt[m]].VdY, koCCP.VdCx, koCCP.VdCy);
if (kdDist < kdDistPrev)
{
kdDistPrev = kdDist;
}
}
//dxprimeSquared[PListInt[m]] = distprev * distprev;
kdDxPrimeSquared[m] = kdDistPrev * kdDistPrev; // dxprimesquared value is actually for point PListInt[m]
kdDxSquared += kdDistPrev * kdDistPrev;
}
// select the center according to probability d(x')^2/(d()^2
kdRandom = koRand.NextDouble( );
kdSumProbab = 0;
for (int n = 0; n < kdDxPrimeSquared.Length; n++)
{
kdSumProbab += (kdDxPrimeSquared[n] / kdDxSquared);
if (kdRandom <= kdSumProbab)
{
// choose this PList[PListInt[n]] as the next cluster center
koCP = new ClusterCenterPoint {
VdCx = aoPList[koPListInt[n]].VdX, VdCy = aoPList[koPListInt[n]].VdY
};
koCP.ViClusterID = i;
koPListInt.RemoveAt(n); // remove the number that has been selected so that it does not get selected again
aoCList.Add(koCP);
break;
}
}
}
}
public static int MDoKMeans(int aiNumClusters,
ref List <MyPoint> aoPList,
ref List <ClusterCenterPoint> aoCL,
double adMaxError, int aiMaxIterations, bool abDoKmeansPlusPlus = false)
{
List <ClusterCenterPoint> koCList = null;
List <ClusterCenterPoint> koCListNew = null;
ClusterCenterPoint koCPNew;
double kdError = double.MaxValue;
double kdErr = 0;
int kiIteration = 0;
int kiC0Count;
int kiC1Count;
int kiC2Count;
int[] kiCCount;
if (abDoKmeansPlusPlus == false)
{
MInitializeCentersRandomlyFromGivenPoints(aoPList, ref koCList, aiNumClusters);
}
else
{
MInitializeCentersRandomlyFromKPP(aoPList, ref koCList, aiNumClusters);
}
while ((kiIteration < aiMaxIterations) || (kdError < adMaxError))
{
Task koFinal;
Task[] koTask = new Task[aoPList.Count];
koCListNew = new List <ClusterCenterPoint>();
kiCCount = new int[koCList.Count];
foreach (ClusterCenterPoint koCP in koCList)
{
koCPNew = new ClusterCenterPoint( );
koCListNew.Add(koCPNew);
koCPNew.VdCx = 0;
koCPNew.VdCy = 0;
}
for (int i = 0; i < aoPList.Count; i++)
{
koTask[i] = Task.Factory.StartNew((aoP) =>
{
MyPoint koP = ( MyPoint )aoP;
int kiK = 0;
double kdPrevDist = double.MaxValue;
double kdDist;
foreach (ClusterCenterPoint koCP in koCList)
{
kdDist = MFindDistance(koP.VdX, koP.VdY, koCP.VdCx, koCP.VdCy);
if (kdDist < kdPrevDist)
{
kdPrevDist = kdDist;
koP.ViClusterId = kiK;
}
kiK++;
}
koCListNew[koP.ViClusterId].VdCx += koP.VdX;
koCListNew[koP.ViClusterId].VdCy += koP.VdY;
kiCCount[koP.ViClusterId]++;
}, aoPList[i]);
}
koFinal = Task.Factory.ContinueWhenAll(koTask, (aoTask) =>
{
// ---------------Recompute cluster centers-------------------
int kiKnew = 0;
foreach (ClusterCenterPoint koCP in koCListNew)
{
koCP.VdCx = koCP.VdCx / kiCCount[kiKnew];
koCP.VdCy = koCP.VdCy / kiCCount[kiKnew];
kiKnew++;
}
//------------------end recompute cluster centers-----------------
//---------------see if new centers are different from previous---
kdErr = 0;
for (int i = 0; i < koCList.Count; i++)
{
kdErr += ((koCListNew[i].VdCx - koCList[i].VdCx) * (koCListNew[i].VdCx - koCList[i].VdCx) +
(koCListNew[i].VdCy - koCList[i].VdCy) * (koCListNew[i].VdCy - koCList[i].VdCy));
}
});
// determine which cluster each point belongs to
kiC0Count = (from koP in aoPList where koP.ViClusterId == 0 select koP).ToList <MyPoint>( ).Count;
kiC1Count = (from koP in aoPList where koP.ViClusterId == 1 select koP).ToList <MyPoint>( ).Count;
kiC2Count = (from koP in aoPList where koP.ViClusterId == 2 select koP).ToList <MyPoint>( ).Count;
if (kdErr < adMaxError)
{
break;
}
koCList.Clear( );
koCList = koCListNew;
kiIteration++;
}
aoCL = koCList;
return(kiIteration);
}
public static void InitializeCentersRandomlyFromKPP(List <MyPoint> PList, ref List <ClusterCenterPoint> CList, int numClusters)
{
Random rand = new Random((int)DateTime.Now.Ticks);
CList = new List <ClusterCenterPoint>();
List <int> PListInt = new List <int>();
for (int i = 0; i < PList.Count; i++)
{
PListInt.Add(i);
}
//step1: of KPP - choose a center randomly from given set of points
int num = rand.Next(PListInt.Count);
ClusterCenterPoint cp = new ClusterCenterPoint
{
Cx = PList[num].X,
Cy = PList[num].Y
};
cp.ClusterID = 0;
PListInt.RemoveAt(num); // remove the number that has been selected so that it does not get selected again
CList.Add(cp);
for (int i = 1; i < numClusters; i++)
{
// Step2: Compute D(x)^2 where D(x) is the distance of x from closest centers chosen
double dxSquared = 0;
double[] dxprimeSquared = new double[PListInt.Count];
for (int m = 0; m < PListInt.Count; m++)
{
double distprev = double.MaxValue;
foreach (ClusterCenterPoint ccp in CList)
{
double dist = FindDistance(PList[PListInt[m]].X, PList[PListInt[m]].Y, ccp.Cx, ccp.Cy);
if (dist < distprev)
{
distprev = dist;
}
}
//dxprimeSquared[PListInt[m]] = distprev * distprev;
dxprimeSquared[m] = distprev * distprev; // dxprimesquared value is actually for point PListInt[m]
dxSquared += distprev * distprev;
}
// select the center according to probability d(x')^2/(d()^2
double randNum = rand.NextDouble();
double sumProbab = 0;
for (int n = 0; n < dxprimeSquared.Length; n++)
{
sumProbab = sumProbab + dxprimeSquared[n] / dxSquared;
if (randNum <= sumProbab)
{ // choose this PList[PListInt[n]] as the next cluster center
ClusterCenterPoint cpp = new ClusterCenterPoint
{
Cx = PList[PListInt[n]].X,
Cy = PList[PListInt[n]].Y
};
cpp.ClusterID = i;
PListInt.RemoveAt(n); // remove the number that has been selected so that it does not get selected again
CList.Add(cpp);
break;
}
}
}
}
public static int DoKMeans(int numClusters, ref List <MyPoint> PList, ref List <ClusterCenterPoint> CL, double maxError, int maxIterations, bool doKmeansPlusPlus = false)
{
List <ClusterCenterPoint> CList = null;
if (doKmeansPlusPlus == false)
{
InitializeCentersRandomlyFromGivenPoints(PList, ref CList, numClusters);
}
else
{
InitializeCentersRandomlyFromKPP(PList, ref CList, numClusters);
}
double error = double.MaxValue;
int iteration = 0;
while ((iteration < maxIterations) || (error < maxError))
{
// determine which clusetr each point belongs to
foreach (MyPoint p in PList)
{
// determine which cluster it belongs to
int k = 0;
double prevDist = double.MaxValue;
foreach (ClusterCenterPoint cp in CList)
{
double dist = FindDistance(p.X, p.Y, cp.Cx, cp.Cy);
if (dist < prevDist)
{
prevDist = dist;
p.ClusterId = k;
}
k++;
}
}
int c0count = (from p in PList where p.ClusterId == 0 select p).ToList <MyPoint>().Count;
int c1count = (from p in PList where p.ClusterId == 1 select p).ToList <MyPoint>().Count;
int c2count = (from p in PList where p.ClusterId == 2 select p).ToList <MyPoint>().Count;
// ---------------Recompute cluster centers-------------------
List <ClusterCenterPoint> CListNew = new List <ClusterCenterPoint>();
int[] CCount = new int[CList.Count];
foreach (ClusterCenterPoint cp in CList)
{
ClusterCenterPoint cpnew = new ClusterCenterPoint();
CListNew.Add(cpnew);
cpnew.Cx = 0;
cpnew.Cy = 0;
}
foreach (MyPoint p in PList)
{
CListNew[p.ClusterId].Cx += p.X;
CListNew[p.ClusterId].Cy += p.Y;
CCount[p.ClusterId]++;
}
int knew = 0;
foreach (ClusterCenterPoint cp in CListNew)
{
cp.Cx = cp.Cx / CCount[knew];
cp.Cy = cp.Cy / CCount[knew];
knew++;
}
//------------------end recompute cluster centers-----------------
//---------------see if new centers are different from previous---
double err = 0;
for (int i = 0; i < CList.Count; i++)
{
err = err + ((CListNew[i].Cx - CList[i].Cx) * (CListNew[i].Cx - CList[i].Cx) + (CListNew[i].Cy - CList[i].Cy) * (CListNew[i].Cy - CList[i].Cy));
}
if (err < maxError)
{
break;
}
CList.Clear();
CList = CListNew;
iteration++;
}
CL = CList;
return(iteration);
}