mstknnclust implements the MST-kNN clustering algorithm, which determines the number of clusters automatically by recursively intersecting the Minimum Spanning Tree (MST) and k-Nearest Neighbor (kNN) proximity graphs.
# From CRAN
install.packages("mstknnclust")
# Development version from GitHub
# install.packages("devtools")
devtools::install_github("jorgeklz/package-mstknnclust")library(mstknnclust)
# Load the Indo-European languages dataset
data("dslanguages")
# Run clustering (only a distance matrix is needed)
results <- mst.knn(dslanguages)
# Results
results$cnumber # number of clusters
results$partition # cluster assignments
results$network # igraph object
# Plot
library(igraph)
plot(results$network,
vertex.size = 5,
vertex.color = components(results$network)$membership,
layout = layout_with_fr(results$network, niter = 10000))Full documentation and vignettes are available at the pkgdown site.
Inostroza-Ponta, M. (2008). An Integrated and Scalable Approach Based on Combinatorial Optimization Techniques for the Analysis of Microarray Data. Ph.D. thesis, University of Newcastle.
GPL-2
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.