dataset = read.csv('02_Boston_Regression.csv')
library(dplyr)
library(randomForest)
data_nomiss = dataset %>%
select( CRIM,ZN,INDUS,CHAS,NOX,RM,AGE,DIS,RAD,TAX,PTRATIO,B,LSTAT,MEDV) %>%
na.omit()
regressor_rf_t = randomForest(MEDV ~., data = data_nomiss, mtry = 6,
ntree = 755, nodesize = 9)
library(shiny)
library(shinythemes)
# Create the user interface (ui) where you will take the input and display the output
ui <- fluidPage(theme = shinytheme("cosmo"),
navbarPage(
"MEDV Prediction",
tabPanel("Navbar 1",
sidebarPanel(
tags$h3("Enter the details of the customer:"),
#radioButtons("CRIM", "CRIM: LESS THAN 0.5 PUT 0 OTHERWISE 1", choiceNames=c('1', '0'), choiceValues = c('1','0')),
selectInput("CRIM", "CRIM 0 - 0.5 ", c("0 - 0.5"=0,
"0.5 - 1"=1)),
#numericInput("Age", "Age Group 1 - 7", 1, min=1, max=7),
#sliderInput("ZN", "ZN 0-100", 1, 9, 1),
sliderInput('ZN','ZN', min = 0,max = 100,value = 50, step = 0.1),
sliderInput('INDUS','INDUS', min = 0, max = 30, value = 15, step = 0.01),
#sliderInput('CHAS','CHAS', min = 0, max = 1, value = 0.5, step = 0.0001),
selectInput("CHAS", "CHAS 0 - 0.5 ", c("0 - 0.5"=0,
"0.5 - 1"=1)),
sliderInput('NOX','NOX', min = 0, max = 10, value = 5, step = 0.0001),
sliderInput('RM','RM', min = 0, max = 100, value = 50, step = 0.00001),
sliderInput('AGE','AGE', min = 0, max = 100, value = 50, step = 0.001),
sliderInput('DIS','DIS', min = 0, max = 100, value = 50, step = 0.00001),
selectInput('RAD','RAD', c("1"=1,
"2"=2,
"3"=3,
"4"=4,
"5"=5,
"6"=6,
"7"=7,
"8"=8,
"24"=24,
"666"=666)),
sliderInput('TAX','TAX',min = 0, max = 1000, value = 500, step = 0.001),
sliderInput('PTRARIO','PTRARIO', min = 0, max = 25, value = 15, step = 0.001),
sliderInput('B','B', min = 0, max = 400, value = 200, step = 0.001),
sliderInput('LSTAT','LSTAT', min = 0, max = 40, value = 20, step = 0.0001),
#numericInput("Income", "Income Group 1 - 9", 1, min=1, max=9),
#numericInput("Tenure", "Tenure in No. of Years", 0),
actionButton("Predict", "Predict MEDV"),
HTML("<br> <br>"),
actionButton("ResetInputs", "Reset"),
), # sidebarPanel
mainPanel(
h1("Predicted Profit"),
h4("Using Random Forest"),
verbatimTextOutput("txtout"),
h4("The selected MEDV was"),
verbatimTextOutput("incoutput")
) # mainPanel
), # Navbar 1, tabPanel
tabPanel("Navbar 2", "This panel is left blank"),
tabPanel("Navbar 3", "This panel is left blank")
) # navbarPage
) # fluidPage
# Define server function
server <- function(input, output, session) {
data = reactive({
data.frame(CRIM = as.integer(input$CRIM),
ZN = as.numeric(input$ZN),
INDUS = input$INDUS,
CHAS = input$CHAS,
NOX = input$NOX,
RM = input$RM,
AGE = input$AGE,
DIS = input$DIS,
TAX = input$TAX,
PTRATIO = input$PTRARIO,
B = input$B,
RAD = input$RAD,
LSTAT = input$LSTAT,
)
})
observeEvent(input$Predict, {
output$txtout = renderText ({
predict(regressor_rf_t, data())
})
output$incoutput=renderText({
input$MEDV
})
})
observeEvent(input$ResetInputs, {
updateRadioButtons(session,"CRIM", selected='1')
updateRadioButtons(session,"CHAS", selected='1')
updateRadioButtons(session,"RAD", selected='1')
updateNumericInput(session, "ZN", value=1)
updateNumericInput(session, "INDUS", value=1)
updateNumericInput(session, "NOX", value=0)
updateNumericInput(session, "RM", value=0)
updateNumericInput(session, "AGE", value=0)
updateNumericInput(session, "DIS", value=0)
updateNumericInput(session, "TAX", value=0)
updateNumericInput(session, "PTRARIO", value=0)
updateNumericInput(session, "B", value=0)
updateNumericInput(session, "LSTAT", value=0)
output$txtout = renderText ({ })
})
}
# Create Shiny object
shinyApp(ui = ui, server = server)
Welcome and sorry about the troubles you're having with your Shiny app.
Right now this isn't much to go on. It's not clear what help you need with your Shiny app. And then the app provided isn't a minimal reproducible example.
Barret's debugging and reprex guide is a good place to start.
If you need to follow-up here, please do with a shiny reprex. For example your app refers to a file that we don't have access to, you can set up a small version of that with something like dput.