Confusion Matrix "
In CMShiny: Interactive Document for Working with Confusion Matrix

knitr::opts_chunk$set(echo = TRUE)
library(shinyMatrix)
library(Matrix)
library(epitools)
library(caret)
library(e1071)

```r sidebarPanel(h6("Edit the Predictive Classes (in Rows) and Actual Classes(in Columns)"), uiOutput("mat"), uiOutput("pos"), plotOutput("CMVis"), downloadButton("downloadPlot", "Download Confusion Matrix Plot"), downloadButton("downloaddata", "Download dataset")) mainPanel( #h6("Edit the Predictive Classes (in Rows) and Actual Classes(in Columns)"), # uiOutput("mat"), # uiOutput("pos"),

plotOutput("CMVis"),

verbatimTextOutput("results"),

h6("", tags$img(src ="K.JPG", height= 400, width=400))

)

output$mat <- renderUI({ matrixInput( "myMatrix", value = matrix(c(5,1,1,3),2,2,dimnames = list(c("Class1","Class2"),c("Class1","Class2"))),

   rows = list(names= TRUE,editableNames = TRUE),
   cols = list( names = TRUE,editableNames = TRUE),
   copy = TRUE,
   paste = TRUE,
   class = 'numeric'
 )

})

output$pos <- renderUI({ CT = matrix(input$myMatrix,nrow = 2, ncol = 2) row.names(CT) = row.names(input$myMatrix) colnames(CT) = colnames(input$myMatrix) dataset = expand.table(CT) colnames(dataset)= c("Predicted","Actual") selectInput("positive",label = "Select the Positive Class",choices = c(levels(dataset$Predicted))) }) output$results <- renderPrint({ CT = matrix(input$myMatrix,nrow = 2, ncol = 2)

 row.names(CT) = row.names(input$myMatrix)
 colnames(CT) = colnames(input$myMatrix)
 dataset = expand.table(CT)
 colnames(dataset)= c("Predicted","Actual")

 print(confusionMatrix(dataset$Predicted,dataset$Actual,positive = input$positive ))

}) output$CMVis <- renderPlot({ CT = matrix(input$myMatrix,nrow = 2, ncol = 2) row.names(CT) = row.names(input$myMatrix) colnames(CT) = colnames(input$myMatrix) dataset = expand.table(CT) colnames(dataset)= c("Predicted","Actual")

ctable <- as.table(matrix(CT, nrow = 2, byrow = FALSE)) fourfoldplot(ctable, color = c("#CC6666", "#99CC99"), conf.level = 0, margin = 1, main = "Confusion Matrix")

# trellis.par.set(caretTheme()) # liftobj = lift(Actual~Predicted,data = dataset) # plot(liftobj) # plot(liftobj,auto.key = list(columns =1,lines = TRUE,points = FALSE)) })

datasetInput1 <- reactive({ CT = matrix(input$myMatrix,nrow = 2, ncol = 2) row.names(CT) = row.names(input$myMatrix) colnames(CT) = colnames(input$myMatrix) dataset = expand.table(CT) colnames(dataset)= c("Predicted","Actual") dataset = dataset

}) output$downloaddata <- downloadHandler( filename = function() { filetitle = paste("dataset") paste(filetitle, ".csv", sep = "") }, content = function(file) {

   write.csv(datasetInput1(), file, row.names = FALSE)
 }

)

output$downloadPlot<- downloadHandler( filename = function() { paste("ConfusionMatPlot", ".png", sep = "") }, content = function(file) { png(file) CT = matrix(input$myMatrix,nrow = 2, ncol = 2) row.names(CT) = row.names(input$myMatrix) colnames(CT) = colnames(input$myMatrix) dataset = expand.table(CT) colnames(dataset)= c("Predicted","Actual")

ctable <- as.table(matrix(CT, nrow = 2, byrow = FALSE)) fourfoldplot(ctable, color = c("#CC6666", "#99CC99"), conf.level = 0, margin = 1, main = "Confusion Matrix") dev.off() })