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ui.R
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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://shiny.rstudio.com
#
library(shiny)
library(markdown)
shinyUI(
navbarPage(
"Peer Review Project for devdataprod-011",
tabPanel(
"Rubric",
includeMarkdown("Rubric.md")
), # End tabPanel
tabPanel(
"Problem Selection",
includeMarkdown("Description.md")
), # End tabPanel
tabPanel(
"Exploration",
sidebarLayout(
sidebarPanel(
radioButtons(
"Country",
"Survey Country:",
c("Jordan", "Palestine", "Algeria", "Morroco",
"Lebanon", "Yemen")
),
selectInput('param1',
"Chart 1 Parameter",
c("Age" = "age",
"Education" = "education",
"Married" = "married",
"Religion" = "religion",
"Employed" = "employed",
"Sex" = "sex",
"Internet" = "internet"),
selected="age"
),
selectInput('param2',
"Chart 2 Parameter",
c("Age" = "age",
"Education" = "education",
"Married" = "married",
"Religion" = "religion",
"Employed" = "employed",
"Sex" = "sex",
"Internet" = "internet"),
selected="education"
),
hr(),
helpText("Data from Arab Barometer (2006-2007)")
),
mainPanel(
plotOutput('bar'),
textOutput('param1'),
hr(),
plotOutput('bar2')
)
) # End sidebarLayout
), # End tabPanel
tabPanel(
"Application",
verticalLayout(
sidebarLayout(
sidebarPanel(
sliderInput(
"trainFraction",
"Fraction for Training Set",
min=0,
max=1,
value=.6
),
actionButton("doIt", "Redo Training"),
hr(),
helpText("Change the proportion of data you
would like to use for training and submit.
to re-calculate the decision tree.")
),
mainPanel(
plotOutput('classificationTree')
)
), # End sidebarLayout
hr(),
sidebarLayout(
sidebarPanel(
actionButton('testPrediction', 'Test Prediction'),
hr(),
helpText("Press the Test Prediction button
to see how accurate the model is.")
),
mainPanel(
tableOutput("predictResults"),
splitLayout(
tableOutput("predictOverall"),
tableOutput("predictClass")
)
)
) # End sidebarLayout
) # End of verticalLayout
) # End tabPanel
) # End navbarPage
) # End shinyUI