public PCMSolution(FCMSolution init, MethodInputResponse input, int clustersCount)
: base(input, clustersCount)
{
eta = new double[clustersNumber];
D = new double[clustersNumber, methodInput.InputObjects.Count];
// initialize cluster prototypes (as a result of FCM):
for (int i = 0; i < clustersNumber; i++)
{
clusterPrototypes[i] = new InputObject("");
clusterPrototypes[i].Dimensions = init.ClusterPrototypes[i].Dimensions;
}
// initialize primary memberships (the same way):
for (int i = 0; i < methodInput.InputObjects.Count; i++)
for (int j = 0; j < clustersNumber; j++)
primaryMemberships[j, i] = init.PrimaryMemberships[j, i];
setD();
setTarget();
}
public void Run()
{
MethodInputResponse inputParams = GetInput();
//get offsets for output
int afterPcmOffset = inputParams.InputObjects.Count + inputParams.dimensionsLowerBounds.Count + 10;
for( int clustersNumber = 3; clustersNumber <= MAX_CLUSTERS_NUMBER; clustersNumber++)
{
ShowIndicesTitles(afterPcmOffset * 2, clustersNumber);
//run FCM to tune initial clusters centers and type-1 memberships
FCMSolution FCM = new FCMSolution(inputParams, clustersNumber);
FCM.DegreeOfFuzziness = 1.5;
int fcmIterationsCounter = 0;
double oldFcmTarget = double.PositiveInfinity;
// start FCM iterations
while (oldFcmTarget > FCM.Target)
{
FCM.UpdateClusterPrototypes();
oldFcmTarget = FCM.Target;
FCM.UpdatePrimaryMemberships();
fcmIterationsCounter++;
Application.DoEvents();
}
//have some output after FCM
//ShowResults(FCM, clustersNumber, inputParams, fcmIterationsCounter, 0, "Best FCM with m = " + FCM.DegreeOfFuzziness);
//run PCM now, using the FCM output
PCMSolution PCM = new PCMSolution(FCM, inputParams, clustersNumber);
PCM.estimateEta();
// iterate m:
PCM.DegreeOfFuzziness = MIN_M_VALUE;
int finalIterationsCounter = 0;
ValidityIndex kwonIndex = new ValidityIndex(IndexType.Kwon);
ValidityIndex partitionIndex = new ValidityIndex(IndexType.PartitionIndex);
ValidityIndex xieBeniIndex = new ValidityIndex(IndexType.XieBeni);
ValidityIndex xieBeni2Index = new ValidityIndex(IndexType.XieBeni2);
kwonIndex.SetCurrentValue(PCM.GetKwonIndex(), PCM.DegreeOfFuzziness);
partitionIndex.SetCurrentValue(PCM.GetPartitionIndex(), PCM.DegreeOfFuzziness);
xieBeniIndex.SetCurrentValue(PCM.GetXieBeniIndex(), PCM.DegreeOfFuzziness);
xieBeni2Index.SetCurrentValue(PCM.GetXieBeni2Index(), PCM.DegreeOfFuzziness);
while (PCM.DegreeOfFuzziness < MAX_M_VALUE)
{
RunPcm(PCM, ref finalIterationsCounter);
kwonIndex.SetCurrentValue(PCM.GetKwonIndex(), PCM.DegreeOfFuzziness);
partitionIndex.SetCurrentValue(PCM.GetPartitionIndex(), PCM.DegreeOfFuzziness);
xieBeniIndex.SetCurrentValue(PCM.GetXieBeniIndex(), PCM.DegreeOfFuzziness);
xieBeni2Index.SetCurrentValue(PCM.GetXieBeni2Index(), PCM.DegreeOfFuzziness);
ShowIndex(afterPcmOffset*2, clustersNumber, 1, PCM.DegreeOfFuzziness, PCM.DegreeOfFuzziness);//m
ShowIndex(afterPcmOffset*2, clustersNumber, (int)kwonIndex.IndexType, kwonIndex.CurrentValue, PCM.DegreeOfFuzziness);
//ShowIndex(afterPcmOffset, clustersNumber, (int)IndexType.PartitionCoefficient, PCM.GetPartitionCoefficient(), PCM.DegreeOfFuzziness);
ShowIndex(afterPcmOffset*2, clustersNumber, (int)partitionIndex.IndexType, partitionIndex.CurrentValue, PCM.DegreeOfFuzziness);
ShowIndex(afterPcmOffset*2, clustersNumber, (int)xieBeniIndex.IndexType, xieBeniIndex.CurrentValue, PCM.DegreeOfFuzziness);
//ShowIndex(afterPcmOffset, clustersNumber, (int)IndexType.ExtendedXieBeni, PCM.GetExtendedXBIndex(), PCM.DegreeOfFuzziness);
//ShowIndex(afterPcmOffset, clustersNumber, (int)IndexType.ExtendedKwon, PCM.GetExtendedKwonIndex(), PCM.DegreeOfFuzziness);
ShowIndex(afterPcmOffset*2, clustersNumber, (int)xieBeni2Index.IndexType, xieBeni2Index.CurrentValue, PCM.DegreeOfFuzziness);
PCM.DegreeOfFuzziness += DEGREE_OF_FUZZINESS_STEP;
}
kwonIndex.SummarizeBounds();
xieBeniIndex.SummarizeBounds();
partitionIndex.SummarizeBounds();
//get upper and lower bounds
//double ultimateUpper = Math.Min(Math.Min(kwonIndex.UpperBound, xieBeniIndex.UpperBound), partitionIndex.UpperBound);
// double ultimateLower = Math.Max(Math.Max(kwonIndex.LowerBound, xieBeniIndex.LowerBound), partitionIndex.LowerBound);
double ultimateUpper = Math.Max(Math.Max(kwonIndex.UpperBound, xieBeniIndex.UpperBound), partitionIndex.UpperBound);
double ultimateLower = Math.Min(Math.Min(kwonIndex.LowerBound, xieBeniIndex.LowerBound), partitionIndex.LowerBound);
//display the bounds of m:
ShowBounds(clustersNumber, xieBeniIndex, kwonIndex, partitionIndex, ultimateLower, ultimateUpper);
//boundary solutions:
// left:
PCMSolution leftSolution = new PCMSolution(FCM, inputParams, clustersNumber);
leftSolution.estimateEta();
leftSolution.DegreeOfFuzziness = ultimateLower;
RunPcm(leftSolution, ref finalIterationsCounter);
// right:
PCMSolution rightSolution = new PCMSolution(FCM, inputParams, clustersNumber);
rightSolution.estimateEta();
rightSolution.DegreeOfFuzziness = ultimateUpper;
RunPcm(rightSolution, ref finalIterationsCounter);
double avgUZoneArea = 0;
int baseOffset = (int) Math.Round(afterPcmOffset * 2 + Enum.GetNames(typeof(IndexType)).Count() + (MAX_M_VALUE - MIN_M_VALUE)/DEGREE_OF_FUZZINESS_STEP);
for (int currentCluster = 0; currentCluster < clustersNumber; currentCluster++)
{
double uZoneArea = PCMSolution.GetUZoneArea(leftSolution.PrimaryMemberships, rightSolution.PrimaryMemberships, currentCluster);
ShowUZoneArea(baseOffset + currentCluster, currentCluster.ToString(), clustersNumber, uZoneArea);
avgUZoneArea += uZoneArea;
}
ShowUZoneArea(baseOffset + clustersNumber, "avg", clustersNumber, avgUZoneArea / clustersNumber);
ShowResults(leftSolution, clustersNumber, inputParams, Enum.GetValues(typeof(IndexType)).Length, "Left bound. m = " + leftSolution.DegreeOfFuzziness);
ShowResults(rightSolution, clustersNumber, inputParams, afterPcmOffset + Enum.GetValues(typeof(IndexType)).Length, "Right bound. m = " + rightSolution.DegreeOfFuzziness);
}
ReleaseExcelStuff();
}