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# Clustering Guide

Use these guides for NVIDIA cuVS clustering APIs that group related vectors or build graph structures from pairwise relationships.

- [K-Means](/user-guide/api-guides/clustering-guide/k-means): partition vectors into a fixed number of clusters, often for scalable vector-search partitioning.
- [Gaussian Mixture Model](/user-guide/api-guides/clustering-guide/gaussian-mixture-model): fit a probabilistic mixture of Gaussians for soft, shape-aware clustering and density estimation.
- [Single-linkage](/user-guide/api-guides/clustering-guide/single-linkage): build hierarchical clusters from nearest-neighbor relationships.
- [Spectral Clustering](/user-guide/api-guides/clustering-guide/spectral-clustering): use graph structure and spectral methods to find clusters with more complex shapes.

## Docs

- [K-Means](https://docs.nvidia.com/cuvs/user-guide/api-guides/clustering-guide/k-means.md)
- [Gaussian Mixture Model](https://docs.nvidia.com/cuvs/user-guide/api-guides/clustering-guide/gaussian-mixture-model.md)
- [Single-linkage](https://docs.nvidia.com/cuvs/user-guide/api-guides/clustering-guide/single-linkage.md)
- [Spectral Clustering](https://docs.nvidia.com/cuvs/user-guide/api-guides/clustering-guide/spectral-clustering.md)