Update src/clustering_quality.jl

Co-authored-by: Alexey Stukalov <[email protected]>

src/clustering_quality.jl

@@ -10,7 +10,7 @@ Compute chosen quality index value for a hard clustering.
  - `data::AbstractMatrix`: ``d×n`` data matrix with each column representing one ``d``-dimensional data point
  - `centers::AbstractMatrix`: ``d×k`` matrix with cluster centers represented as columns
  - `assignments::AbstractVector{Int}`: ``n`` vector of point assignments (cluster indices)
- - `kmeans_clustering::KmeansResult`: the output of kmeans method
+ - `clustering::ClusteringResult`: the output of the clustering method
  - `distance::SemiMetric=SqEuclidean()`: `SemiMetric` object that defines the distance between the data points
  - `quality_index::Symbol`: quality index to calculate; see below for the supported options