R: Create clustering configurations.

compare_clusterings_configs {dtwclust} | R Documentation

## Create clustering configurations.

### Description

Create configurations for `compare_clusterings()`

### Usage

    compare_clusterings_configs(
      types = c("p", "h", "f"),
      k = 2L,
      controls = NULL,
      preprocs = pdc_configs("preproc", none = list()),
      distances = pdc_configs("distance", dtw_basic = list()),
      centroids = pdc_configs("centroid", default = list()),
      no.expand = character(0L)
    )

### Arguments

`types` | Clustering types. It must be any combination of (possibly abbreviated): partitional, hierarchical, fuzzy, tadpole.
`k` | A numeric vector with one or more elements specifying the number of clusters to test.
`controls` | A named list of tsclust-controls. `NULL` means defaults. See details.
`preprocs` | Preprocessing configurations. See details.
`distances` | Distance configurations. See details.
`centroids` | Centroid configurations. See details.
`no.expand` | A character vector indicating parameters that should not be expanded between `pdc_configs()` configurations. See examples.

### Details

Preprocessing, distance and centroid configurations are specified with the helper function `pdc_configs()`, refer to the examples in `compare_clusterings()` to see how this is used.

The controls list may be specified with the usual tsclust-controls functions. The names of the list must correspond to "partitional", "hierarchical", "fuzzy" or "tadpole" clustering. Again, please refer to the examples in `compare_clusterings()`.

### Value

A list for each clustering type, each of which includes a data frame with the computed and merged configurations. Each data frame has an extra attribute `num.configs` specifying the number of configurations.

### Examples

    # compare this with leaving no.expand empty
    compare_clusterings_configs(
        distances = pdc_configs("d", dtw_basic = list(window.size = 1L:2L, norm = c("L1", "L2"))),
        centroids = pdc_configs("c", dba = list(window.size = 1L:2L, norm = c("L1", "L2"))),
        no.expand = c("window.size", "norm")
    )

[Package dtwclust version 5.5.7 Index]