/// <summary>
/// UseKMeans is an extension that call KMeans through LearningAPI
/// </summary>
/// <param name="api">the LearningAPI object</param>
/// <param name="settings">the desired clustering settings</param>
/// <returns></returns>
public static LearningApi UseKMeans(this LearningApi api, ClusteringSettings settings, double[] maxDistance = null)
{
var alg = new KMeansAlgorithm(settings.Clone(), maxDistance);
api.AddModule(alg, "Rbm");
return(api);
}
/// <summary>
/// UseKMeans is an extansion that call KMeans through LearningAPI
/// </summary>
/// <param name="api">the LearningAPI object</param>
/// <param name="settings">the desired clustering settings</param>
/// <returns></returns>
public static LearningApi UseKMeans(this LearningApi api, ClusteringSettings settings, double[][] centroids = null, double[] maxDistance = null)
{
var alg = new KMeans(settings, centroids, maxDistance);
api.AddModule(alg, "Rbm");
return(api);
}
/// <summary>
/// Clonses settings object.
/// </summary>
/// <returns></returns>
internal ClusteringSettings Clone()
{
ClusteringSettings sett = this.MemberwiseClone() as ClusteringSettings;
if (this.InitialCentroids != null)
{
List <double[]> copyCentroids = new List <double[]>();
foreach (var centroid in this.InitialCentroids)
{
Array arr = new double[centroid.Length];
centroid.CopyTo(arr, 0);
copyCentroids.Add(arr as double[]);
}
sett.InitialCentroids = copyCentroids.ToArray();
}
return(sett);
}
/// <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);
}