将新操作添加到Apriori算法背后的闪亮应用程序

将新操作添加到Apriori算法背后的闪亮应用程序,r,shiny,scatter-plot,apriori,arules,R,Shiny,Scatter Plot,Apriori,Arules,我有这个代码(它正常工作): 库(闪亮) 图书馆(阿鲁莱斯维兹) 用户界面 library(shiny) library(arulesViz) ui <- shinyUI(fluidPage( titlePanel(""), tabsetPanel( tabPanel("Experiment 1", sidebarPanel( # Changed values of the widgets numericInput("su

我有这个代码(它正常工作):

库(闪亮)
图书馆(阿鲁莱斯维兹)
用户界面
library(shiny)
library(arulesViz)

ui <- shinyUI(fluidPage(

   titlePanel(""),

 tabsetPanel(
   tabPanel("Experiment 1",
      sidebarPanel(
        # Changed values of the widgets
          numericInput("supp", "Vložte hodnotu support", 0.01, 
                       min = 0.01, max = 0.8, step = 0.01),
          numericInput("conf", "Vložte hodnotu confidence", 0.01, 
                       min = 0.01, max = 0.8, step = 0.01))
  )
 ), 
  mainPanel(
     plotOutput("scatterPlot")
     )
  )
)

server <- shinyServer(function(input, output) {

  data("Groceries")

    rules.all <- reactive({
    apriori(Groceries, parameter=list(support=input$supp, confidence=input$conf))
  })


 output$scatterPlot = renderPlot({ 
    plot(rules.all(), method = 'scatterplot')
  })
})

shinyApp(ui = ui, server = server)
quality(rules.all) <- round(quality(rules.all), digits=3)
top.support <- sort(rules.all, decreasing = TRUE, na.last = NA, by = "support") rules.sorted = sort(rules.all, by="lift")

subset.matrix = is.subset(rules.sorted, rules.sorted)

subset.matrix[lower.tri(subset.matrix, diag=T)] = NA

redundant = colSums(subset.matrix, na.rm=T) >= 1

rules.pruned = rules.sorted[!redundant]

rules.all = rules.pruned

rules.sorted = sort(rules.all, by="lift") 

rules.all = rules.sorted