在Shiny

时间:2016-09-22 01:29:03

标签: r shiny

我正在开发一个Shiny应用程序,让用户按需选择依赖/自变量,然后执行C5.0生成摘要和树形图。但是,生成绘图时出现错误消息。有谁知道解决方案?请找到代码:

library(shiny)

ui <- fluidPage(
  titlePanel('Plotting Decision Tree'),
  sidebarLayout(
    sidebarPanel(
      h3('iris data'),
      uiOutput('choose_y'),
      uiOutput('choose_x'),
      actionButton('c50', label = 'Generate C5.0 summary and plot')
    ),
    mainPanel(
      verbatimTextOutput('tree_summary'),
      plotOutput('tree_plot_c50')
    )
  )
)

# server.R
library(shiny)
library(C50)

server <- function(input, output) {
  output$choose_y <- renderUI({
    is_factor <- sapply(iris, FUN = is.factor)
    y_choices <- names(iris)[is_factor]
    selectInput('choose_y', label = 'Choose Target Variable', choices = y_choices)
  })

  output$choose_x <- renderUI({
    x_choices <- names(iris)[!names(iris) %in% input$choose_y]
    checkboxGroupInput('choose_x', label = 'Choose Predictors', choices = x_choices)
  })

  observeEvent(input$c50, {
    c50_fit <- C5.0(as.formula(paste(isolate(input$choose_y), '~', paste(isolate(input$choose_x), collapse = '+'))), data = iris)
    output$tree_summary <- renderPrint(summary(c50_fit))
    output$tree_plot_c50 <- renderPlot({
      plot(c50_fit)
    })
  })
}

shinyApp(ui, server)

1 个答案:

答案 0 :(得分:2)

server.R尝试

function(input, output) {
  output$choose_y <- renderUI({
    is_factor <- sapply(iris, FUN = is.factor)
    y_choices <- names(iris)[is_factor]
    selectInput('choose_y', label = 'Choose Target Variable', choices = y_choices)
  })

  output$choose_x <- renderUI({
    x_choices <- names(iris)[!names(iris) %in% input$choose_y]
    checkboxGroupInput('choose_x', label = 'Choose Predictors', choices = x_choices)
  })

  observeEvent(input$c50, {
    form <- paste(isolate(input$choose_y), '~', paste(isolate(input$choose_x), collapse = '+'))
    c50_fit <- eval(parse(text = sprintf("C5.0(%s, data = iris)", form)))
    output$tree_summary <- renderPrint(summary(c50_fit))
    output$tree_plot_c50 <- renderPlot({
      plot(c50_fit)
    })
  })
}

解释。 plot方法似乎在寻找call返回值的C5.0()元素中指定的术语,并引发错误什么时候找不到它们。在您的情况下,这指的是input对象。解决方法是通过C5.0()构造使用完全指定的公式(例如Species ~ Sepal.Length + Petal.Width)来调用eval(parse(text = ...))