distance_matrix: Distance matrix calculation

In ClusterR: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering

Distance matrix calculation

Description

Distance matrix calculation

Usage

distance_matrix(
  data,
  method = "euclidean",
  upper = FALSE,
  diagonal = FALSE,
  minkowski_p = 1,
  threads = 1
)

Arguments

data	matrix or data frame
method	a string specifying the distance method. One of, euclidean, manhattan, chebyshev, canberra, braycurtis, pearson_correlation, simple_matching_coefficient, minkowski, hamming, jaccard_coefficient, Rao_coefficient, mahalanobis, cosine
upper	either TRUE or FALSE specifying if the upper triangle of the distance matrix should be returned. If FALSE then the upper triangle will be filled with NA's
diagonal	either TRUE or FALSE specifying if the diagonal of the distance matrix should be returned. If FALSE then the diagonal will be filled with NA's
minkowski_p	a numeric value specifying the minkowski parameter in case that method = "minkowski"
threads	the number of cores to run in parallel (if OpenMP is available)

Value

a matrix

Examples

data(dietary_survey_IBS)

dat = dietary_survey_IBS[, -ncol(dietary_survey_IBS)]

dat = distance_matrix(dat, method = 'euclidean', upper = TRUE, diagonal = TRUE)

ClusterR documentation built on June 22, 2024, 10:28 a.m.