/// <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);
}
