DataOrDistances: [1:n,1:d] matrix of dataset to be clustered. It consists of n cases of d-dimensional data points. Every case has d attributes, variables or features. Alternatively, symmetric [1:n,1:n] distance matrix
ClusterNo: A number k which defines k different clusters to be build by the algorithm.
DistanceMethod: See parDist, for example 'euclidean','mahalanobis','manhatten' (cityblock),'fJaccard','binary', 'canberra', 'maximum'. Any unambiguous substring can be given.
ColorTreshold: Draws cutline w.r.t. dendogram y-axis (height), height of line as scalar should be given
...: furter argument to genie like:
thresholdGini Single numeric value in [0,1], threshold for the Gini index, 1 gives the standard single linkage algorithm
Details
Wrapper for Genie algorithm.
Returns
List of - Cls: If, ClusterNo>0: [1:n] numerical vector with n numbers defining the classification as the main output of the clustering algorithm. It has k unique numbers representing the arbitrary labels of the clustering. Otherwise for ClusterNo=0: NULL
Dendrogram: Dendrogram of hierarchical clustering algorithm
Object: Ultrametric tree of hierarchical clustering algorithm
References
[Gagolewski/Bartoszuk, 2016] Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm, Information Sciences, Vol. 363, pp. 8-23, 2016.