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?