KNNConstruction: Building Unweighted K Nearest Neighbor Graph

In XuegongLab/HGC: A fast hierarchical graph-based clustering method

Description

This function builds an Unweighted K Nearest Neighbor (KNN) graph in the input feature space using Euclidean distance metric.

Usage

KNN.Construction(mat, k)

Arguments

mat	the input data saved as a numerical matrix. The columns are the features and the rows are the samples.
k	the number of nearest neighbors for building the KNN graph.

Details

This function builds a KNN graph of the input data. The main function comes from the R package RANN.

Value

An n by n binary dgCMatrix object C, where n is the number of input samples. The matrix C is the adjacency matrix of the built KNN graph. C[i,j] = 1 means that there is an edge between sample i and sample j.

Examples

data(Pollen)
Pollen.PCs <- Pollen[["PCs"]]
G <- KNN.Construction(Pollen.PCs)

XuegongLab/HGC documentation built on Dec. 18, 2021, 7:23 p.m.