export_sample_similarity-methods: Extract and export mutual correlation between features.

In familiar: End-to-End Automated Machine Learning and Model Evaluation

Extract and export mutual correlation between features.

Description

Extract and export mutual correlation between features in a familiarCollection.

Usage

export_sample_similarity(
  object,
  dir_path = NULL,
  aggregate_results = TRUE,
  sample_limit = waiver(),
  sample_cluster_method = waiver(),
  sample_linkage_method = waiver(),
  export_dendrogram = FALSE,
  export_collection = FALSE,
  ...
)

## S4 method for signature 'familiarCollection'
export_sample_similarity(
  object,
  dir_path = NULL,
  aggregate_results = TRUE,
  sample_limit = waiver(),
  sample_cluster_method = waiver(),
  sample_linkage_method = waiver(),
  export_dendrogram = FALSE,
  export_collection = FALSE,
  ...
)

## S4 method for signature 'ANY'
export_sample_similarity(
  object,
  dir_path = NULL,
  aggregate_results = TRUE,
  sample_limit = waiver(),
  sample_cluster_method = waiver(),
  sample_linkage_method = waiver(),
  export_dendrogram = FALSE,
  export_collection = FALSE,
  ...
)

Arguments

object	A familiarCollection object, or other other objects from which a familiarCollection can be extracted. See details for more information.
dir_path	Path to folder where extracted data should be saved. NULL will allow export as a structured list of data.tables.
aggregate_results	Flag that signifies whether results should be aggregated for export.
sample_limit	(optional) Set the upper limit of the number of samples that are used during evaluation steps. Cannot be less than 20. This setting can be specified per data element by providing a parameter value in a named list with data elements, e.g. list("sample_similarity"=100, "permutation_vimp"=1000). This parameter can be set for the following data elements: sample_similarity and ice_data.
sample_cluster_method	The method used to perform clustering based on distance between samples. These are the same methods as for the cluster_method configuration parameter: hclust, agnes, diana and pam. none cannot be used when extracting data for feature expressions. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
sample_linkage_method	The method used for agglomerative clustering in hclust and agnes. These are the same methods as for the cluster_linkage_method configuration parameter: average, single, complete, weighted, and ward. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
export_dendrogram	Add dendrogram in the data element objects.
export_collection	(optional) Exports the collection if TRUE.
...	Arguments passed on to as_familiar_collection familiar_data_names Names of the dataset(s). Only used if the object parameter is one or more familiarData objects. collection_name Name of the collection.

Details

Data is usually collected from a familiarCollection object. However, you can also provide one or more familiarData objects, that will be internally converted to a familiarCollection object. It is also possible to provide a familiarEnsemble or one or more familiarModel objects together with the data from which data is computed prior to export. Paths to the previous files can also be provided.

All parameters aside from object and dir_path are only used if object is not a familiarCollection object, or a path to one.

Value

A list containing a data.table (if dir_path is not provided), or nothing, as all data is exported to csv files.

familiar documentation built on Sept. 30, 2024, 9:18 a.m.