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); } }