HCA {structToolbox} | R Documentation |
HCA method class. Calculate a hierarchical clustering for the input data.
HCA( dist_method = "euclidean", cluster_method = "complete", minkowski_power = 2, factor_name, ... )
dist_method |
The distance method to use for clustering. Can be any one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". Default is "euclidean". |
cluster_method |
The clustering method to use. Can be any one of "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median" or "centroid". Default is 'complete'. |
minkowski_power |
This parameter is only used when |
factor_name |
The sample_meta column to use. |
... |
additional slots and values passed to struct_class |
struct object
D = iris_DatasetExperiment() M = HCA(factor_name='Species') M = model_apply(M,D)