How to create a cluster plot in R?

Question

How can I create a cluster plot in R without using clustplot?

I am trying to get to grips with some clustering (using R) and visualisation (using HTML5 Canvas).

Answer 1

Did you mean something like this? Sorry but i know nothing about HTML5 Canvas, only R... But I hope it helps...

First I cluster the data using kmeans (note that I did not cluster the distance matrix), than I compute the distance matix and plot it using cmdscale. Then I add colors to the MDS-plot that correspond to the groups identified by kmeans. Plus some nice additional graphical features.

You can access the coordinates from the object created by cmdscale.

### some sample data
require(vegan)
data(dune)

# kmeans
kclus <- kmeans(dune,centers= 4, iter.max=1000, nstart=10000)

# distance matrix
dune_dist <- dist(dune)

# Multidimensional scaling
cmd <- cmdscale(dune_dist)

# plot MDS, with colors by groups from kmeans
groups <- levels(factor(kclus$cluster))
ordiplot(cmd, type = "n")
cols <- c("steelblue", "darkred", "darkgreen", "pink")
for(i in seq_along(groups)){
  points(cmd[factor(kclus$cluster) == groups[i], ], col = cols[i], pch = 16)
}

# add spider and hull
ordispider(cmd, factor(kclus$cluster), label = TRUE)
ordihull(cmd, factor(kclus$cluster), lty = "dotted")

Answer 2

Here you can find one graph to analyze cluster results, "coordinate plot", within "clusplot" package.

It is not based on PCA. It uses function scale to have all the variables means in a range of 0 to 1, so you can compare which cluster holds the max/min average for each variable.

install.packages("devtools") ## To be able to download packages from github
library(devtools)
install_github("pablo14/clusplus")
library(clusplus)

## Create k-means model with 3 clusters
fit_mtcars=kmeans(mtcars,3)

## Call the function
plot_clus_coord(fit_mtcars, mtcars)

This post explains how to use it.