ShinieR Interaction with <<-

server.R

library(shiny)
library(ggplot2)
library(reshape2)
library(randomForest)

df = ChickWeight 
n = nrow(df)
perfdf = data.frame(ntree=as.numeric(), mse_train=as.numeric(), mse_test=as.numeric())
count = 0 

shinyServer(function(input, output) {

  output$runs <- renderText({
    train <- df[sample(n),][1:478,]
    test <- df[sample(n),][479:n,]
    rf = randomForest(weight ~ Time + Diet, data=train, ntree = input$ntree)
    train$mse <- (predict(rf, train) - train$weight)^2
    test$mse <- (predict(rf, test) - test$weight)^2
    
    perfdf <<- rbind(perfdf, data.frame(ntree=input$ntree, mse_train=mean(train$mse), mse_test=mean(test$mse)))
    count <<- count + 1 
    paste("random forest count :", count)
  })
  
  output$perf <- renderPlot({
    input$ntree
    perfdf <- melt(perfdf, id.vars = c("ntree"),
         variable.name = "variable", value.name = "value"
    )
    p = ggplot() + geom_point(data=perfdf, aes(ntree, value, colour=variable)) 
    # p = p + facet_grid( variable ~ . , scales = "free_y")
    p = p + stat_smooth(data=perfdf, aes(ntree, value, colour=variable), se = FALSE) 
    # geom_smooth(data=perfdf, aes(ntree, value, colour=variable)) 
    p + ggtitle("train set performance")
  }, height=400)
  
})

ui.R

library(shiny)

shinyUI(fluidPage(

  # Application title
  titlePanel("Shiny App"),

  # Sidebar with a slider input for number of bins
  sidebarLayout(
    sidebarPanel(
      sliderInput("ntree",
                  "give the number of trees:",
                  min = 1,
                  max = 200,
                  value = 10, step=1)
    ),

    # Show a plot of the generated distribution
    mainPanel(
      textOutput("runs"),
      plotOutput("perf")
    )
  )
))