Are there any deterministic clustering methods implemented in Julia? For example:

```
using Clustering
using DataFrames
df = DataFrame(subject=1:10, height=rand(10), weight=rand(10))
julia> groups = kmeans(Matrix(df[:, 2:3])', 2).assignments
10-element Array{Int64,1}:
1
1
2
1
1
1
2
1
1
1
julia> groups = kmeans(Matrix(df[:, 2:3])', 2).assignments
10-element Array{Int64,1}:
1
1
1
2
2
2
1
1
1
1
```

Is there a clustering algorithm in Julia that will result in the same clusters for this problem each time? Or is there a way to set the seed via `Random.seed!()`

that would result in the same clusters with k-means?

Any recommendations as to how to approach a problem like this where a deterministic outcome is very important would be much appreciated!