static void Main(string[] args)
{
#region Combine path
string folder = ".\\..\\..\\..\\Data";
string fileName = "example.xlsx";
string path = Path.Combine(folder, fileName);
#endregion
IKMeansBuilder kMeansBuilder = new KMeansBuilder();
IKMeans kMeans;
kMeans = kMeansBuilder
.Init(new KMeansInitialization())
.SetNumberOfClusters(2)
.Build();
IDataView data = DataReaderExcel.ReadDataFromExcel(
path: path,
hasHeader: true,
worksheet: 3,
startColumn: 2);
var clustered = kMeans.FitPredict(data);
IQualityMeasurement qualityMeasurementAlgorithm = new IndexC();
var res = qualityMeasurementAlgorithm.EvaluateQuality(clustered, new EuclideanDistance());
Console.WriteLine(res);
Console.Read();
}
public ActionResult <float> EvaluateClustering(DataViewClustered dataViewClustered)
{
IQualityMeasurement evaluator = new IndexC();
var res = evaluator.EvaluateQuality(dataViewClustered, new EuclideanDistance());
return(Ok(res));
}
void Start()
{
Regex rg = new Regex(regex, RegexOptions.Multiline | RegexOptions.Singleline);
List <IndexC> indexList = new List <IndexC>();
Match match = rg.Match(result);
Debug.LogError(match.Value);
while (match.Success)
{
IndexC icc = new IndexC();
icc.startIndex = match.Index;
icc.endIndex = match.Index + match.Length;
indexList.Add(icc);
match = match.NextMatch();
}
for (int i = 0, maxi = indexList.Count; i < maxi; ++i)
{
Debug.LogError("S_index : " + indexList[i].startIndex + " E_index" + indexList[i].endIndex);
}
}
