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Source header: cuvs/preprocessing/spectral_embedding.hpp

Types

preprocessing::spectral_embedding::params

Parameters for spectral embedding algorithm

Spectral embedding is a dimensionality reduction technique that uses the eigenvectors of the graph Laplacian to embed data points into a lower-dimensional space. This technique is particularly useful for non-linear dimensionality reduction and clustering tasks.

struct params {
  int n_components;
  int n_neighbors;
  bool norm_laplacian;
  bool drop_first;
  float tolerance;
  std::optional<uint64_t> seed;
};

Fields

NameTypeDescription

n_components	int	The number of components to reduce the data to.
n_neighbors	int	The number of neighbors to use for the nearest neighbors graph.
norm_laplacian	bool	Whether to normalize the Laplacian matrix. If true, uses the normalized graph Laplacian (D^(-1/2) L D^(-1/2)). If false, uses the unnormalized graph Laplacian (L = D - W). Normalized Laplacian often leads to better results for clustering tasks.
drop_first	bool	Whether to drop the first eigenvector. The first eigenvector of the normalized Laplacian is constant and uninformative. Setting this to true drops it from the embedding. This is typically set to true when norm_laplacian is true.
tolerance	float	Tolerance for the eigenvalue solver. The tolerance for the eigenvalue solver. This is used to determine when to stop the eigenvalue solver.
seed	std::optional<uint64_t>	Random seed for reproducibility. Controls the random number generation for k-NN graph construction and eigenvalue solver initialization. Use the same seed value to ensure reproducible results across runs.

Spectral Embedding

preprocessing::spectral_embedding::transform

Perform spectral embedding on input dataset

void transform(raft::resources const& handle,
params config,
raft::device_matrix_view<float, int, raft::row_major> dataset,
raft::device_matrix_view<float, int, raft::col_major> embedding);

This function computes the spectral embedding of the input dataset by:

Constructing a k-nearest neighbors graph from the input data
Computing the graph Laplacian (normalized or unnormalized)
Finding the eigenvectors corresponding to the smallest eigenvalues
Using these eigenvectors as the embedding coordinates

Parameters

NameDirectionTypeDescription

handle	in	raft::resources const&	RAFT resource handle for managing CUDA resources
config	in	params	Parameters controlling the spectral embedding algorithm
dataset	in	raft::device_matrix_view<float, int, raft::row_major>	Input dataset in row-major format [n_samples x n_features]
embedding	out	raft::device_matrix_view<float, int, raft::col_major>	Output embedding in column-major format [n_samples x n_components]

Returns

void

Additional overload: preprocessing::spectral_embedding::transform

Perform spectral embedding using a precomputed connectivity graph

void transform(raft::resources const& handle,
params config,
raft::device_coo_matrix_view<float, int, int, int> connectivity_graph,
raft::device_matrix_view<float, int, raft::col_major> embedding);

This function computes the spectral embedding from a precomputed sparse connectivity graph (e.g., from a k-NN search or custom similarity matrix). This is useful when you want to use a custom graph construction method or when you have a precomputed similarity/affinity matrix.

The function:

Converts the COO matrix to the graph Laplacian
Computes eigenvectors of the Laplacian
Returns the eigenvectors as the embedding

Parameters

NameDirectionTypeDescription

handle	in	raft::resources const&	RAFT resource handle for managing CUDA resources
config	in	params	Parameters controlling the spectral embedding algorithm (n_neighbors parameter is ignored when using precomputed graph)
connectivity_graph	in	raft::device_coo_matrix_view<float, int, int, int>	Precomputed sparse connectivity/affinity graph in COO format representing weighted connections between samples
embedding	out	raft::device_matrix_view<float, int, raft::col_major>	Output embedding in column-major format [n_samples x n_components]

Returns

void

Spectral Embedding

Types

preprocessing::spectral_embedding::params

Spectral Embedding

preprocessing::spectral_embedding::transform

Preprocessing Quantize Scalar

Selection Select K

1	struct params {
2	int n_components;
3	int n_neighbors;
4	bool norm_laplacian;
5	bool drop_first;
6	float tolerance;
7	std::optional<uint64_t> seed;
8	};

1	void transform(raft::resources const& handle,
2	params config,
3	raft::device_matrix_view<float, int, raft::row_major> dataset,
4	raft::device_matrix_view<float, int, raft::col_major> embedding);