This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 123]

Cclustering::kmeans::AfkMc2Seeder< T >	AFK-MC2 seeder (Bachem, Lucic, Hassani, Krause, NeurIPS 2016)
Cclustering::hdbscan::AutoMstBackend< T >	MST backend that dispatches between Prim, Boruvka, and NN-Descent on input shape
Cclustering::index::AutoRangeIndex< T >	Range-index policy that picks KDTree below a dimension threshold and BruteForcePairwise above it
Cclustering::kmeans::AutoSeeder< T, Mode >	Seeder that picks between greedy k-means++ and AFK-MC2 against workload shape
Cclustering::NDArray< T, N, L >::BaseAccessor	Inner class providing base functionality for element access in NDArray
Cclustering::NDArray< T, N, L >::ConstAccessor	Provides read-only access to NDArray elements
Cclustering::NDArray< T, N, L >::Accessor	Provides read-write access to NDArray elements
Cclustering::BinaryHeap< Key, Val >	Binary min-heap of (key, val) pairs ordered on `key`
Cclustering::hdbscan::BoruvkaMstBackend< T >	KDTree-accelerated Boruvka MST backend over mutual-reachability distances
Cclustering::BruteForcePairwise< T >	Range-index backend that builds the full eps-neighborhood adjacency in one fused pairwise sweep
Cclustering::HDBSCAN< T, MstBackend >::CondensedTreeView	Read-only view over the condensed-tree result
Cclustering::math::distance::CosineTag	Tag selecting the cosine distance metric (1 - cos(angle))
Cclustering::DBSCAN< T, QueryModel >	Density-based clustering over the eps-neighborhood graph produced by a clustering::index::RangeIndex backend
Cclustering::IndexedHeap< Key, Val, Idx >::Entry	One heap entry
Cclustering::math::GemmPlan< T, Backend >	Reusable GEMM plan: packs `B` once at construction, amortizes the packing cost across repeated `execute` calls with varying `A`
Cclustering::kmeans::GreedyKmppSeeder< T >	Greedy k-means++ seeder
Cclustering::HDBSCAN< T, MstBackend >	Hierarchical density-based clustering over mutual-reachability distances
Cclustering::IndexedHeap< Key, Val, Idx >	Binary min-heap keyed on `Key` with O(1) handle-to-position lookup
Cclustering::KDTree< T, distanceType, LeafSize, AllocT >	Implements a KDTree data structure
Cclustering::KDTreeNode	Node in a KDTree, sharing the same struct shape between internals and leaves
Cclustering::KMeans< T, Algo, Seeder >	Lloyd-family k-means
Cclustering::index::NnDescentIndex< T >::KnnEntry	Per-node kNN entry returned by neighbors. Squared Euclidean distance carried as `T`
Cclustering::LinearAllocator< T >
Cclustering::kmeans::LloydFusedGemm< T >	Fused-argmin-GEMM Lloyd driver
Cclustering::math::distance::ManhattanTag	Tag selecting the Manhattan (L1) metric: sum of absolute differences
Cclustering::hdbscan::MstEdge< T >	One edge of the minimum spanning tree of mutual-reachability distances
Cclustering::hdbscan::MstOutput< T >	Frozen output contract of every MST backend
Cclustering::NDArray< T, N, L >	Represents a multidimensional array (NDArray) of a fixed number of dimensions N and element type T
Cclustering::NewAllocator< T >	Thin wrapper over `new` T / `delete` that satisfies the library's allocator concept
Cclustering::index::NnDescentIndex< T >	Approximate `k` -nearest-neighbor graph via the NN-Descent algorithm (Dong, Charikar, Li 2011) with random-projection-tree initialization
Cclustering::hdbscan::NnDescentMstBackend< T >	Approximate minimum-spanning-tree backend over mutual-reachability distance via an NN-Descent-built kNN graph plus Kruskal, with a connectivity fallback that closes any disconnected components
Cclustering::hdbscan::NnDescentMstConfig	Tuning knobs for the NN-Descent MST backend
Cclustering::math::pcg64	128-bit state for the PCG-XSL-RR 64-bit output generator (Melissa O'Neill)
Cclustering::math::Pool	Thin injection wrapper around a `BS::light_thread_pool`
Cclustering::hdbscan::PrimMstBackend< T >	Exact minimum-spanning-tree backend over mutual-reachability distance, streaming Prim
Cclustering::Range	Half-open index range with optional positive step for slicing an NDArray axis
Cclustering::math::distance::SqEuclideanTag	Tag selecting the squared Euclidean metric
Cclustering::UnionFind< Idx >	Disjoint-set-union with iterative path compression and union-by-rank
Cclustering::math::xoshiro256ss	256-bit state for Vigna & Blackman's xoshiro256** generator