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#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(nproc)
classifiers <- c("logistic", "penlog", "svm", "randomforest",
"lda", "nb", "ada", "tree")
# Define server logic required to draw a histogram
server <- function(input, output, session) {
output$downloadData <- downloadHandler(
filename = 'ytest.hat.csv',
content = function(file) {
inFilex <- input$xfile
if (is.null(inFilex))
return(NULL)
x = as.matrix(read.csv(inFilex$datapath, header = input$headerx))
inFiley <- input$yfile
if (is.null(inFiley))
return(NULL)
y = unlist(read.csv(inFiley$datapath, header = input$headery))
fit = nproc(x, y, method = input$method, delta = input$delta, split = input$split)
inFilextestfile <- input$xtestfile
if (is.null(inFilextestfile))
return(NULL)
xtest = as.matrix(read.csv(inFilextestfile$datapath, header = input$headerxtest))
fit = npc(x, y, method = input$method, alpha = input$alpha, delta = input$delta, split = input$split)
predy = predict(fit, newx = xtest)$pred.label
write.table(predy, file, sep = ',', row.names = FALSE, col.names = FALSE)
}
)
output$plot1 = renderPlot({
inFilex <- input$xfile
if (is.null(inFilex))
return(NULL)
x = as.matrix(read.csv(inFilex$datapath, header = input$headerx))
inFiley <- input$yfile
if (is.null(inFiley))
return(NULL)
y = unlist(read.csv(inFiley$datapath, header = input$headery))
fit = nproc(x, y, method = input$method, delta = input$delta, split = input$split)
plot(fit)
})
##Plot the nproc curve
}
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