/// <summary> /// Installs the KMeanFunctionRecognitionModule in the LearningApi pipeline. /// </summary> /// <param name="api"></param> /// <param name="settings"></param> /// <returns></returns> public static LearningApi UseKMeansFunctionRecognitionModule(this LearningApi api, ClusteringSettings settings) { var alg = new KMeansFunctionRecognitionAlgorithm(settings); api.AddModule(alg, "KMeanFunctionRecognitionModule"); return(api); }
public void Test_OptimalNumberOfClusters_TwoFunctions() { int numAttributes = 3; int MinNumClusters = 2; int MaxNumClusters = 10; int maxCount = 300; double[] Fmins; // directory to load string loadDirectory = rootFolder + "Functions\\"; string functionA = "SIN_SIN X"; string functionB = "SIN_COS X"; // load Data double[][] loadedSimFunctions1 = Helpers.LoadFunctionData(loadDirectory + functionA + "\\NRP5-10\\" + functionA + " SimilarFunctions Normalized NRP5-10.csv"); double[][] loadedSimFunctions2 = Helpers.LoadFunctionData(loadDirectory + functionB + "\\NRP5-10\\" + functionB + " SimilarFunctions Normalized NRP5-10.csv"); ClusteringSettings settings = new ClusteringSettings(maxCount, MinNumClusters, numAttributes, KmeansAlgorithm: 2); int recNumClusters = KMeansFunctionRecognitionAlgorithm.OptimalNumberOfClusters_TwoFunctions(loadedSimFunctions1, loadedSimFunctions2, settings, MinNumClusters, MaxNumClusters, out Fmins); }