Shiny on K-means Clustering

Develop Data Products Assessment

Terence Liu, Ph.D candidate
NJU

Aim & Usage

This application is to cluster the rock dataset by k-means, with various algorithms. The user can set the varibles, number of cluster and algorithm

  1. The paired varibles of the dataset
  2. Number of cluster
  3. Algorithm

ur.R

shinyUI(pageWithSidebar(
  headerPanel('Rock k-means clustering using different algorithms'),
  sidebarPanel(
    h5('This application is to cluster the rock dataset by k-means, using different
       algorithms. The user can set the varibles, number of cluster and algorithm'),

    selectInput('xcol', 'X Variable', names(rock)[-1]),
    selectInput('ycol', 'Y Variable', names(rock)[-1],
                selected=names(rock)[2]),
    numericInput('clusters', 'Cluster count', 3,
                 min = 1, max = 6),
    selectInput('algo', 'Algorithm', c("Hartigan-Wong", "Lloyd", "Forgy","MacQueen"))

  ),
  mainPanel(
    plotOutput('plot1')
  )
))

## Error in eval(expr, envir, enclos): 没有"shinyUI"这个函数

server.R

palette(rainbow(6))

shinyServer(function(input, output, session) {
  selectedData <- reactive({
    rock[, c(input$xcol, input$ycol)]
  })
  clusters <- reactive({
    kmeans(selectedData(), input$clusters, algorithm=input$algo)
  }) 
  output$plot1 <- renderPlot({
    par(mar = c(5.1, 4.1, 0, 1))
    plot(selectedData(),
         col = clusters()$cluster,
         pch = 20, cex = 3)
    points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
  }) 
})

## Error in eval(expr, envir, enclos): 没有"shinyServer"这个函数

To run it