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# This is the user-interface definition of a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://www.rstudio.com/shiny/
#
library(shiny)
shinyUI(
fluidPage(
# Application title
titlePanel("Machine Learning Application"),
hr(),
# Show a plot of the generated distribution
tabsetPanel(
tabPanel(title="Machine Learning Application",
sidebarPanel(
h3("Choose Model Type"), selectInput("modeltype",label='Select Model from the options',choices=
list("Artificial Neural Network"=1, "Support Vector Machine"=2 )) ,hr(),
h3("Model Parameters"),
fileInput('file1', h5('Choose Training Data File (CSV)'),
accept=c('text/csv',
'text/comma-separated-values,text/plain',
'.csv')),
tags$hr(),
splitLayout( div(checkboxInput('header', 'Header', TRUE),
radioButtons('sep', 'Separator',
c(Comma=',',
Semicolon=';',
Tab='\t'),
',')),
radioButtons('quote', 'Quote',
c(None='',
'Double Quote'='"',
'Single Quote'="'"),
'"')),
hr(),
uiOutput(outputId = "features"),
textOutput(outputId = "test_checkbox"),
div(textOutput(outputId = "feature_error"), style="color:red;font-weight:200"),
uiOutput(outputId = "ann_parameters")
,width =5
),
mainPanel(
#Panel only displayed after file is read
conditionalPanel (condition = "output.ann_parameters !== null" , div( h4("Preview Of Read Data: "), helpText("Showing 10 Columns only"),
#This is the preview of read file
tableOutput(outputId = "contents")
,hr() ,h4("Model Plot"),plotOutput("ann_plot"),hr(),
h4("Model Overview"), uiOutput("ann_printstats"),hr(),h4("Model Output") ,tableOutput(outputId = "ann_result") ) )
, width=7) #main Panel ends here
) #TabPanel ends here
,id=c("MLAPP" ), type="tabs" ,position="above" ) #The code for all tabs (tabsetPanel) ends here
) #fluidPage ends here
) #the app ends here