The documentation of kmeans
of the Clustering.jl
states that:
help?> kmeans
search: kmeans kmeans! kmeans_opts KmeansResult
kmeans(X, k, [...]) -> KmeansResult
K-means clustering of the d×n data matrix X (each column of X is a d-dimensional data point) into k clusters.
Does this mean rows of X
represent the features and columns represent data samples?