private void ThreadMethod(int start, int end, int min)
{
for (int i = start; i < end; i++)
{
int cCount = i;
ClusterResult clusterresult = null;
switch (this.MethodMode)
{
case 0: clusterresult = SingleStart(cCount, ref this.WaitObj.Flags[i - min]); break;
case 1: clusterresult = SingleStartWithWeight(cCount, ref this.WaitObj.Flags[i - min]); break;
}
ClusterAssessReport_BWP clusterassessreport = Assess.GetBWP(Data, clusterresult, Distences);
lock (this.SyObject)
{
this.FinalReport.HisResult.Add(clusterresult);
this.FinalReport.HisReport.Add(clusterassessreport);
if (clusterassessreport.AvgBWP > this.Score)
{
this.Score = clusterassessreport.AvgBWP;
FinalReport.FanialResult = clusterresult;
FinalReport.FanialReport = clusterassessreport;
}
}
}
if (Barobj != null)
{
Barobj.RemoveParticipant();
}
}
public static ClusterAssessReport_BWP GetBWP(IDataTable <DataRow> data, ClusterResult result, double[,] distence)
{
int cCount = result.cCount;
int dataCount = data.RowCount;
int paraCount = result.Properties.Length;
var classnumber = result.ClassNumbers;
var properties = result.Properties;
int[] eachClusterCount = result.CountEachCluster;
double[,] bc = new double[dataCount, cCount];
double[] b = new double[dataCount];
double[] w = new double[dataCount];
double[] bwp = new double[dataCount];
double avgBwp = 0;
ClusterAssessReport_BWP report = new ClusterAssessReport_BWP();
for (int i = 0; i < dataCount - 1; i++)
{
for (int j = i + 1; j < dataCount; j++)
{
int cj = classnumber[j];
int ci = classnumber[i];
double temp = distence[i, j];
int tempcountj = eachClusterCount[cj];
int tempcounti = eachClusterCount[ci];
if (ci == cj)
{
temp = temp / (tempcountj - 1);
w[i] += temp;
w[j] += temp;
}
else
{
bc[i, cj] += temp / tempcountj;
bc[j, ci] += temp / tempcounti;
}
}
}
for (int i = 0; i < dataCount; i++)
{
var iclass = classnumber[i];
double tempb = Double.PositiveInfinity;
for (int j = 0; j < iclass; j++)
{
double t = bc[i, j];
if (t < tempb && t != 0)
{
tempb = t;
}
}
for (int j = iclass + 1; j < cCount; j++)
{
double t = bc[i, j];
if (t < tempb && t != 0)
{
tempb = t;
}
}
b[i] = tempb;
double tempw = w[i];
bwp[i] = (tempb - tempw) / (tempb + tempw);
avgBwp += bwp[i];
}
avgBwp = avgBwp / dataCount;
report.AvgBWP = avgBwp;
report.B = b;
report.W = w;
report.BWP = bwp;
return(report);
}
public ClusterResult SingleStartWithWeight(int cCount, ref int flag)
{
DateTime starttime = DateTime.Now;
var result = new ClusterResult();
double[,] center = new double[cCount, ParaCount];
double[] w = new double[ParaCount];
int[] reCount;
int i, j, k;
for (i = 0; i < ParaCount; i++)
{
w[i] = (double)1 / ParaCount;
}
int[] classnumber = new int[DataCount];
int count = 0;
bool same;
int fail;
double odd = 2;
switch (InitialMode)
{
case 0: InitCenter(cCount, center); break;
case 1: InitCenterSPSS(cCount, center); break;
case 2: InitCenterAvg(cCount, odd, center); break;
}
while (true)
{
reCount = new int[cCount];
same = true;
for (i = 0; i < DataCount; i++)
{
double[] len = new double[cCount];
int min = 0;
for (j = 0; j < cCount; j++)
{
for (k = 0; k < ParaCount; k++)
{
len[j] += w[k] * Math.Pow(Data[i, Properties[k]].ConvertToDouble() - center[j, k], 2);
}
if (len[j] < len[min])
{
min = j;
}
}
if (same && classnumber[i] != min)
{
same = false;
}
classnumber[i] = min;
reCount[min]++;
}
if (InitialMode == 2 && count == 0)
{
fail = 0;
for (i = 0; i < cCount; i++)
{
if (reCount[i] == 0)
{
fail++;
if (fail > cCount / 10)
{
break;
}
}
}
if (fail > cCount / 10)
{
odd = odd / 2;
InitCenterAvg(cCount, odd, center);
continue;
}
}
count++;
if (count >= MaxCount || same)
{
break;
}
ResetCenterAndWeights(cCount, classnumber, reCount, center, w);
flag++;
}
result.Centers = center;
result.ClassNumbers = classnumber;
result.Weights = w;
result.cCount = cCount;
result.Properties = Properties;
result.LoopCount = count;
result.CountEachCluster = reCount;
DateTime endtime = DateTime.Now;
result.CostTime = (endtime - starttime).TotalMilliseconds;
flag = MaxCount;
return(result);
}