HCA {structToolbox} | R Documentation

## HCA method class

### Description

HCA method class. Calculate a hierarchical clustering for the input data.

### Usage

    HCA(
      dist_method = "euclidean",
      cluster_method = "complete",
      minkowski_power = 2,
      factor_name,
      ...
    )

### Arguments

`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 `dist_method = 'minkowski'`.
`factor_name` | The sample_meta column to use.
`...` | additional slots and values passed to struct_class

### Value

struct object

### Examples

    D = iris_DatasetExperiment()
    M = HCA(factor_name='Species')
    M = model_apply(M,D)

[Package structToolbox version 0.99.8 Index]