Struct faiss::ProgressiveDimClusteringParameters

struct ProgressiveDimClusteringParameters : public faiss::ClusteringParameters

Subclassed by faiss::ProgressiveDimClustering

Public Functions

ProgressiveDimClusteringParameters()

Public Members

int progressive_dim_steps

number of incremental steps

bool apply_pca

apply PCA on input

int niter = 25

number of clustering iterations

int nredo = 1

redo clustering this many times and keep the clusters with the best objective

bool verbose = false

bool spherical = false

whether to normalize centroids after each iteration (useful for inner product clustering)

bool int_centroids = false

round centroids coordinates to integer after each iteration?

bool update_index = false

re-train index after each iteration?

bool frozen_centroids = false

Use the subset of centroids provided as input and do not change them during iterations

int min_points_per_centroid = 39

If fewer than this number of training vectors per centroid are provided, writes a warning. Note that fewer than 1 point per centroid raises an exception.

int max_points_per_centroid = 256

to limit size of dataset, otherwise the training set is subsampled

int seed = 1234

seed for the random number generator. negative values lead to seeding an internal rng with std::high_resolution_clock.

size_t decode_block_size = 32768

when the training set is encoded, batch size of the codec decoder

bool check_input_data_for_NaNs = true

whether to check for NaNs in an input data

bool use_faster_subsampling = false

Whether to use splitmix64-based random number generator for subsampling, which is faster, but may pick duplicate points.