# Clustering

Clustering is implemented in two classes, HCA and K-Means.
Using classes for clustering simplifies explorative analysis as for example different visualisations can be generated without recalculating the clusters.

## Hierarchical cluster analysis

```{eval-rst}
.. autoclass::
    autoprot.analysis.clustering.HCA
    :members:
```

## K-Means clustering

```{eval-rst}
.. autoclass:: 
    autoprot.analysis.clustering.KMeans
    :members:
```