get_highest_prune_param_embedding {ClustAssess} | R Documentation |
Calculate the highest pruning parameter for the SNN graph given Embedding
Description
Given an embedding, the function calculates the highest pruning parameter for the SNN graph that preserves the connectivity of the graph.
Usage
get_highest_prune_param_embedding(embedding, n_neigh)
Arguments
embedding |
A matrix associated with a PCA embedding. Embeddings from other dimensionality reduction techniques (such as LSI) can be used. |
n_neigh |
The number of nearest neighbours. |
Value
The value of the highest pruning parameter.
Note
Given the way the SNN graph is built, the possible values for the pruning
parameter are limited and can be determined by the formula i / (2 * n_neigh - i)
,
where i
is a number of nearest neighbours between 0 and n_neigh
.
Examples
set.seed(2024)
# create an artificial pca embedding
pca_embedding <- matrix(
c(runif(100 * 10), runif(100 * 10, min = 3, max = 4)),
nrow = 200, byrow = TRUE
)
rownames(pca_embedding) <- as.character(1:200)
colnames(pca_embedding) <- paste("PC", 1:10)
get_highest_prune_param_embedding(pca_embedding, 5)
[Package ClustAssess version 1.1.0 Index]