如何解决R语言（Shiny Web应用）中的’参数x为空’错误

我正在尝试学习在R中构建基于机器学习的Shiny界面。我花了几个小时试图解决这个“参数10为空”的错误，但一直没能找到解决办法。我的代码遵循了来自Github的@dataprofessor创建的结构。我非常感谢任何建议、提示和纠正。谢谢！

这是我的代码：

# 导入库
library(shiny)
library(data.table)
library(randomForest)
library(caret)
library(mlbench)
data("Glass")
# 读取RF模型
model <- readRDS("model.rds")
# 训练集
set.seed(345)
train.index=createDataPartition(Glass[,ncol(Glass)],p=0.7,list=FALSE)
train=Glass[train.index,]
#####################################
# 用户界面
#####################################
ui <- pageWithSidebar(
        # 页面头部
    headerPanel('玻璃类型预测器'),
        # 输入值
    sidebarPanel(
        HTML("<h3>输入参数</h4>"),
        sliderInput("RI", label = "折射率", value = mean(train$RI),
                    min = min(train$RI),
                    max = max(train$RI)),
        sliderInput("Na", label = "钠", value = mean(train$Na),
                    min = min(train$Na),
                    max = max(train$Na)),
        sliderInput("Mg", label = "镁", value = mean(train$Mg),
                    min = min(train$Mg),
                    max = max(train$Mg)),
        sliderInput("Al", label = "铝", value = mean(train$Al),
                    min = min(train$Al),
                    max = max(train$Al)),
        sliderInput("Si", label = "硅", value = mean(train$Si),
                    min = min(train$Si),
                    max = max(train$Si)),
        sliderInput("K", label = "钾", value = mean(train$K),
                    min = min(train$K),
                    max = max(train$K)),
        sliderInput("Ca", label = "钙", value = mean(train$Ca),
                    min = min(train$Ca),
                    max = max(train$Ca)),
        sliderInput("Ba", label = "钡", value = mean(train$Ba),
                    min = min(train$Ba),
                    max = max(train$Ba)),
        sliderInput("Fe", label = "铁", value = mean(train$Fe),
                    min = min(train$Fe),
                    max = max(train$Fe)),
                actionButton("submitbutton", "提交", class = "btn btn-primary")
    ),
        mainPanel(
        tags$label(h3('状态/输出')), # 状态/输出文本框
        verbatimTextOutput('contents'),
        tableOutput('tabledata') # 预测结果表
            ))
#####################################
# 服务器
#####################################
server<- function(input, output, session) {
        # 输入数据
    datasetInput <- reactive({
                  df <- data.frame(
            Name = c("折射率",
                     "钠",
                     "镁",
                     "铝",
                     "硅",
                     "钾",
                     "钙",
                     "钡",
                     "铁"),
            Value = as.character(c(input$RI,
                                   input$Na,
                                   input$Mg,
                                   input$Al,
                                   input$Si,
                                   input$K,
                                   input$Ca,
                                   input$Ba,
                                   input$Fe,)),
            stringsAsFactors = FALSE)
                Type <- 5
        df <- rbind(df, Type)
        input <- transpose(df)
        write.table(input,"input.csv", sep=",", quote = FALSE, row.names = FALSE, col.names = FALSE)
                test <- read.csv(paste("input", ".csv", sep=""), header = TRUE)
                Output <- data.frame(Prediction=predict(model,test), round(predict(model,test,type="prob"), 3))
        print(Output)
            })
        # 状态/输出文本框
    output$contents <- renderPrint({
        if (input$submitbutton>0) {
             isolate("计算完成。")
         } else {
            return("服务器已准备好进行计算。")
        }
    })
        # 预测结果表
    output$tabledata <- renderTable({
        if (input$submitbutton>0) {
             isolate(datasetInput())
         }
     })
    }
#####################################
# 创建Shiny应用
#####################################
shinyApp(ui = ui, server = server)

这是model.RDS的代码

library(randomForest)
library(mlbench)
data("Glass")
###########################################################################################################################################
# 随机分割为训练集和测试集
##################
set.seed(345)
train.index=createDataPartition(Glass[,ncol(Glass)],p=0.7,list=FALSE)
train=Glass[train.index,]
test=Glass[-train.index,]
##########################################################################
# 随机森林模型
#######################################################################################################################################################################
model <- randomForest(Type ~ ., data = train, ntree = 500, mtry = 9, importance = TRUE)
model
# 保存模型到RDS文件
saveRDS(model, "model.rds")

回答：

最初的问题是由input$Fe后的一个多余逗号引起的。这导致了第二个问题，即代码所需的test数据框的名称与从输入值构建的名称不匹配。我还需要在构建模型时添加对library(caret)的调用。现在它可以运行了，我可以看到Type被传递到预测调用中。不确定为什么需要这个，因为预测试图得出Type，所以我删除了它。我还删除了input.csv文件的创建，直接创建了测试数据框。

这是完整的app.R。

library(shiny)
library(data.table)
library(randomForest)
library(caret)
library(mlbench)
data("Glass")
# 读取RF模型
model <- readRDS("model.rds")
# 训练集
set.seed(345)
train.index=createDataPartition(Glass[,ncol(Glass)],p=0.7,list=FALSE)
train=Glass[train.index,]
#####################################
# 用户界面
#####################################
ui <- pageWithSidebar(
        # 页面头部
    headerPanel('玻璃类型预测器'),
        # 输入值
    sidebarPanel(
        HTML("<h3>输入参数</h3>"),
        sliderInput("RI", label = "折射率", value = mean(train$RI),
                                min = min(train$RI),
                                max = max(train$RI)),
        sliderInput("Na", label = "钠", value = mean(train$Na),
                                min = min(train$Na),
                                max = max(train$Na)),
        sliderInput("Mg", label = "镁", value = mean(train$Mg),
                                min = min(train$Mg),
                                max = max(train$Mg)),
        sliderInput("Al", label = "铝", value = mean(train$Al),
                                min = min(train$Al),
                                max = max(train$Al)),
        sliderInput("Si", label = "硅", value = mean(train$Si),
                                min = min(train$Si),
                                max = max(train$Si)),
        sliderInput("K", label = "钾", value = mean(train$K),
                                min = min(train$K),
                                max = max(train$K)),
        sliderInput("Ca", label = "钙", value = mean(train$Ca),
                                min = min(train$Ca),
                                max = max(train$Ca)),
        sliderInput("Ba", label = "钡", value = mean(train$Ba),
                                min = min(train$Ba),
                                max = max(train$Ba)),
        sliderInput("Fe", label = "铁", value = mean(train$Fe),
                                min = min(train$Fe),
                                max = max(train$Fe)),
                actionButton("submitbutton", "提交", class = "btn btn-primary")
    ),
        mainPanel(
        tags$label(h3('状态/输出')), # 状态/输出文本框
        verbatimTextOutput('contents'),
        tableOutput('tabledata') # 预测结果表
            ))
#####################################
# 服务器
#####################################
server<- function(input, output, session) {
        # 输入数据
    datasetInput <- reactive({
                  df <- data.frame(
            Name = c("RI",
                     "Na",
                     "Mg",
                     "Al",
                     "Si",
                     "K",
                     "Ca",
                     "Ba",
                     "Fe"),
            Value = as.character(c(input$RI,
                                 input$Na,
                                 input$Mg,
                                 input$Al,
                                 input$Si,
                                 input$K,
                                 input$Ca,
                                 input$Ba,
                                 input$Fe)),
            stringsAsFactors = FALSE)
        input <- transpose(df)
        test = input[2,]
        names(test) = as.character(input[1,])
                Output <- data.frame(Prediction=predict(model,test), round(predict(model,test,type="prob"), 3))
        Output
    })
        # 状态/输出文本框
    output$contents <- renderPrint({
        if (input$submitbutton>0) {
             isolate("计算完成。")
         } else {
            return("服务器已准备好进行计算。")
        }
    })
        # 预测结果表
    output$tabledata <- renderTable({
        if (input$submitbutton>0) {
             isolate(datasetInput())
         }
     })
    }
#####################################
# 创建Shiny应用
#####################################
shinyApp(ui = ui, server = server)

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如何解决R语言（Shiny Web应用）中的’参数x为空’错误

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