public cFeedBackMessage Run()
{
base.Start();
if (!FeedBackMessage.IsSucceed) return FeedBackMessage;
if (this.Input.Count > 1)
{
this.FeedBackMessage = new cFeedBackMessage(false, this);
return this.FeedBackMessage;
}
#region parameters initialization
//object _firstValue = base.ListProperties.FindByName("Number of Clusters");
//int NumOfClusters = 0;
//if (_firstValue == null)
//{
// base.GenerateError("-Number of Clusters- not found !");
// return base.FeedBackMessage;
//}
//try
//{
// cProperty TmpProp = (cProperty)_firstValue;
// NumOfClusters = (int)TmpProp.GetValue();
//}
//catch (Exception)
//{
// base.GenerateError("-Number of Clusters- cast didn't work");
// return base.FeedBackMessage;
//}
#endregion
cMachineLearning MachineLearning = new cMachineLearning(/*cWell.GlobalInfo*/null);
if (ParamAlgoForClustering == null)
ParamAlgoForClustering = MachineLearning.AskAndGetClusteringAlgo();
if (ParamAlgoForClustering == null)
{
FeedBackMessage.IsSucceed = false;
FeedBackMessage.Message = "Invalid Parameters";
return FeedBackMessage;
}
MachineLearning.SelectedClusterer = MachineLearning.BuildClusterer(ParamAlgoForClustering, this.Input);
if (MachineLearning.SelectedClusterer != null)
{
cLinearize L = new cLinearize();
L.SetInputData(this.Input);
L.Run();
cExtendedTable Test = L.GetOutPut();
ClusterEvaluation CE = MachineLearning.EvaluteAndDisplayClusterer(/*richTextBoxInfoClustering*/null,
null,
MachineLearning.CreateInstancesWithoutClass(this.Input));
double[] Assign = CE.getClusterAssignments();
base.Output = new cExtendedTable(this.Input);
cExtendedList CL = new cExtendedList("Class ID");
CL.SetInfo(CE.clusterResultsToString());
base.Output.Add(CL);
for (int i = 0; i < Assign.Length; i++)
base.Output[base.Output.Count-1].Add(Assign[i]);
}
base.End();
return FeedBackMessage;
}
