calc_aris: Construct an ARI matrix storing inter-solution similarities

In metasnf: Meta Clustering with Similarity Network Fusion

Construct an ARI matrix storing inter-solution similarities

Description

This function constructs an ari_matrix class object from a solutions_df class object. The ARI matrix stores pairwise adjusted Rand indices for all cluster solutions as well as a numeric order for the solutions data frame based on the hierarchical clustering of the ARI matrix.

Usage

calc_aris(
  sol_df,
  processes = 1,
  verbose = FALSE,
  dist_method = "euclidean",
  hclust_method = "complete"
)

Arguments

sol_df	Solutions data frame containing cluster solutions to calculate pairwise ARIs for.
processes	Specify number of processes used to complete calculations 1 (default) Sequential processing 2 or higher: Parallel processing will use the future.apply::future_apply to distribute the calculations across the specified number of CPU cores. If higher than the number of available cores, a warning will be raised and the maximum number of cores will be used. max: All available cores will be used. Note that no progress indicator is available during multi-core processing.
verbose	If TRUE, output progress to console.
dist_method	Distance method to use when calculating sorting order to of the matrix. Argument is directly passed into stats::dist. Options include "euclidean", "maximum", "manhattan", "canberra", "binary", or "minkowski".
hclust_method	Agglomerative method to use when calculating sorting order by stats::hclust. Options include "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid".

Value

om_aris ARIs between clustering solutions of an solutions data frame

Examples

dl <- data_list(
    list(subc_v, "subcortical_volume", "neuroimaging", "continuous"),
    list(pubertal, "pubertal_status", "demographics", "continuous"),
    uid = "unique_id"
)

sc <- snf_config(dl, n_solutions = 3)
sol_df <- batch_snf(dl, sc)
calc_aris(sol_df)

metasnf documentation built on April 3, 2025, 5:40 p.m.