anchor.diff:  ## Density based clustering
   
   ### DBSCAN
  +
  +Further information can be found [here](https://fslab.org/content/tutorials/004_clustering_DBSCAN.html).
   
   *)
   //four dimensional clustering with sepal length, petal length, sepal width and petal width
  
positive.code:     - [Silhouette coefficient](#Silhouette-coefficient)
      - [GapStatistics](#GapStatistics)
  
  For demonstration of several clustering methods, the classic iris data set is used, which consists of 150 records, 
  each of which contains four measurements and a species identifier. Since the species identifier occur several times 
  (Iris-virginica, Iris-versicolor, and Iris-setosa), the first step is to generate unique labels:
  
negative.code: #r "nuget: Plotly.NET.Interactive, 2.0.0-beta8"
  #r "nuget: FSharpAux, 1.0.0"
  #r "nuget: FSharp.Stats"
  #r "nuget: Cyjs.NET"
  #endif // IPYNB
  
  (**
  