kNN Classification in ggplot2

ggfortify supports stats::kmeans class. You must explicitly pass original data to autoplot function via data keyword. Because kmeans object doesn't store original data. The result will be automatically colorized by categorized cluster.

Default clustered scatterplot

library(plotly)
library(ggfortify)

set.seed(1)
p <- autoplot(kmeans(USArrests, 3), data = USArrests)

ggplotly(p)

library(plotly)
library(ggfortify)

p <- autoplot(kmeans(USArrests, 3), data = USArrests, label = TRUE, label.size = 3)

ggplotly(p)

Using cluster package

{ggfortify} supports cluster::clara, cluster::fanny, cluster::pam as well as cluster::silhouette classes. Because these instances should contains original data in its property, there is no need to pass original data explicitly.

library(plotly)
library(ggfortify)
library(cluster)

p <- autoplot(clara(iris[-5], 3))

ggplotly(p)

Plotting cluster converx

Specifying frame = TRUE in autoplot for stats::kmeans and cluster::* draws convex for each cluster.

library(plotly)
library(ggfortify)
library(cluster)

p <-  autoplot(fanny(iris[-5], 3), frame = TRUE)

ggplotly(p)

Plotting cluster probability ellipse

If you want probability ellipse, specify whatever supported in ggplot2::stat_ellipse's type keyword via frame.type option.

library(plotly)
library(ggfortify)
library(cluster)

p <- autoplot(pam(iris[-5], 3), frame = TRUE, frame.type = 'norm')

ggplotly(p)

Silhouette plot

library(plotly)
library(ggfortify)
library(cluster)

p <- autoplot(silhouette(pam(iris[-5], 3L)))

ggplotly(p)

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)