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?