PMSTConstruction: Building Unweighted Perturbed Minimum Spanning Tree Graph

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

Description

This function builds an Unweighted Perturbed Minimum Spanning Tree (PMST) graph in the input feature space using Euclidean distance metric.

Usage

PMST.Construction(mat, iter, r)

Arguments

mat	the input data saved as a numerical matrix. The columns are the features and the rows are the samples.
iter	the number of perturbation.
r	the parameter about the strength of the perturbation.

Details

The function builds a PMST graph of the input data. PMST is the combination of a number of MSTs, which are built in the perturbed data spaces.

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 PMST 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 <- PMST.Construction(Pollen.PCs)

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