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ui.R
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# Define UI for application that draws a histogram
ui <- dashboardPage(
skin = "blue",
# Application title
dashboardHeader(title = "Success of Tele-Marketing Call", titleWidth = 350),
# Sidebar with a slider input for number of bins
dashboardSidebar(
width = 350,
sidebarMenu(
style = "font-size: 130%",
menuItem(
"Prediction Dashboard",
tabName = "dashboard",
icon = icon("dashboard")
),
menuItem(
"Decision Tree Summary",
icon = icon("tree"),
tabName = "dt_widget",
badgeColor = "green"
),
menuItem(
"Logistic Regression Summary",
icon = icon("chart-line"),
tabName = "lr_widget",
badgeColor = "green"
),
menuItem(
"KNN Summary",
icon = icon("bezier-curve"),
tabName = "knn_widget",
badgeColor = "green"
),
menuItem(
"Attribute Examples",
icon = icon("user-check"),
tabName = "data_example",
badgeColor = "green"
),
menuItem(
"Attribute Definitions",
icon = icon("glasses"),
tabName = "data_define",
badgeColor = "green"
),
menuItem(
"Glossary",
icon = icon("book-reader"),
tabName = "glossary",
badgeColor = "green"
)
)
),
dashboardBody(fluidPage(
tabItems(
# Prediction Body UI
tabItem(
tabName = "dashboard",
fluidRow(
column(width = 10,
h2(tags$b("Make predictions for new customers:"))),
column(
width = 2,
shiny::actionButton(
inputId = 'git-hub',
class = "pull-right",
# style = "background: #f0f3ff; border-radius: 50%; box-shadow: 6px 6px 10px -1px rgb(0 0 0 / 15%), -6px -6px 10px -1px rgb(255 255 255 / 70%);",
style = "width: 4.5rem; height: 4.5rem; box-shadow:6px 6px 12px #b8b9be, -6px -6px 12px #fff !important; border-radius: 50%; border-color: #D1D9E6; border: .0625rem solid #fafbfe; ",
label = NULL,
icon = icon("github fa-lg"),
onclick ="window.open('https://github.com/mayank7jan/bank-loan-predictor')"
)
)
),
## Reference neomorphism button style
# https://themesberg.com/docs/neumorphism-ui/components/icon-boxes/
fluidRow(
valueBoxOutput("dt_cust_pred_ui"),
valueBoxOutput("lr_cust_pred_ui"),
valueBoxOutput("knn_cust_pred_ui")
),
fluidRow(
style = "font-size: 130%",
box(
width = 4,
collapsible = TRUE,
title = tags$b("DECISION TREE", style = "font-size: 150%"),
tags$hr(),
numericInput(
inputId = "dt_nr_employed",
label = "Number of employees:",
value = 5009,
step = 10
),
radioButtons(
inputId = "dt_poutcome",
label = "Outcome of previous marketing campaign:",
choices = list("failure", "nonexistent", "success"),
selected = "success"
),
hr(),
actionButton(
inputId = "update_dt_button",
label = "Predict",
icon = icon("stopwatch"),
width = '100%',
style = 'font-size:125%; font-variant: small-caps; font-weight: bold;'
)
# hr()
# actionButton(inputId = "copy_button", label = "Make all values similar", icon = icon("copy"),
# width = '100%',
# style = 'font-size:125%; font-variant: small-caps; font-weight: bold;')
),
box(
width = 4,
collapsible = TRUE,
title = tags$b("LOGISTIC REGRESSION", style = "font-size: 150%"),
tags$hr(),
numericInput(
inputId = "lr_nr_employed",
label = "Number of employees:",
value = 5009,
step = 10
),
radioButtons(
inputId = "lr_poutcome",
label = "Outcome of previous marketing campaign:",
choices = list("failure", "nonexistent", "success"),
selected = "success"
),
numericInput(
inputId = "lr_euribor",
label = "Euribor 3 month rate:",
value = 0.635,
step = 0.1
),
numericInput(
inputId = "lr_cons_price_idx",
label = "Consumer price index:",
value = 93.37,
step = 5
),
numericInput(
inputId = "lr_cons_conf_idx",
label = "Consumer confidence index:",
value = -34.8,
step = 0.2
),
numericInput(
inputId = "lr_emp_var_rate",
label = "Employment variation rate:",
value = -1.8,
step = 0.1
),
selectInput(
inputId = "lr_month",
label = "Last contact month of year:",
choices = list(
"mar",
"apr",
"may",
"jun",
"jul",
"aug",
"sep",
"oct",
"nov",
"dec"
),
selected = "mar"
),
sliderInput(
inputId = "lr_previous",
label = "Number of contacts performed before this campagin:",
min = 0,
max = 7,
step = 1,
value = 1
),
numericInput(
inputId = "lr_age",
label = "Age of client:",
value = 30
),
radioButtons(
inputId = "lr_contact",
label = "Contact communication type:",
choices = list("telephone", "cellular"),
selected = "cellular"
),
selectInput(
inputId = "lr_job",
label = "Type of Job:",
choices = list(
'management',
'services',
'admin.',
'blue-collar',
'technician',
'retired',
'student',
'unemployed',
'housemaid',
'self-employed',
'unknown',
'entrepreneur'
),
selected = "technician"
),
radioButtons(
inputId = "lr_dcredit",
label = "Has credit in default?",
choices = list("no", "yes", "unknown"),
selected = "no"
)
),
box(
width = 4,
collapsible = TRUE,
title = tags$b("KNN CLASSIFICATION", style = "font-size: 150%"),
tags$hr(),
numericInput(
inputId = "knn_nr_employed",
label = "Number of employees:",
value = 5009,
step = 10
),
radioButtons(
inputId = "knn_poutcome",
label = "Outcome of previous marketing campaign:",
choices = list("failure", "nonexistent", "success"),
selected = "success"
),
numericInput(
inputId = "knn_euribor",
label = "Euribor 3 month rate:",
value = 0.635,
step = 0.1
),
numericInput(
inputId = "knn_cons_price_idx",
label = "Consumer price index:",
value = 93.37,
step = 5
),
numericInput(
inputId = "knn_cons_conf_idx",
label = "Consumer confidence index:",
value = -40,
step = 0.2
),
numericInput(
inputId = "knn_emp_var_rate",
label = "Employment variation rate:",
value = -1.8,
step = 0.1
),
selectInput(
inputId = "knn_month",
label = "Last contact month of year:",
choices = list(
"mar",
"apr",
"may",
"jun",
"jul",
"aug",
"sep",
"oct",
"nov",
"dec"
),
selected = "apr"
),
sliderInput(
inputId = "knn_previous",
label = "Number of contacts performed before this campagin:",
min = 0,
max = 7,
step = 1,
value = 1
),
numericInput(
inputId = "knn_age",
label = "Age of client:",
value = 30
),
radioButtons(
inputId = "knn_contact",
label = "Contact communication type:",
choices = list("telephone", "cellular"),
selected = "cellular"
),
selectInput(
inputId = "knn_job",
label = "Type of Job:",
choices = list(
'management',
'services',
'admin.',
'blue-collar',
'technician',
'retired',
'student',
'unemployed',
'housemaid',
'self-employed',
'unknown',
'entrepreneur'
),
selected = "technician"
),
radioButtons(
inputId = "knn_dcredit",
label = "Has credit in default?",
choices = list("no", "yes", "unknown"),
selected = "no"
)
)
)
),
# Decision Tree Body UI
tabItem(tabName = "dt_widget",
h2(tags$b(
"Decision Tree Summary"
)),
tabBox(
width = 12,
#id = "dt_fig",
tabPanel(
title = tags$b("Decision Tree Structure") ,
solidHeader = TRUE,
withSpinner(plotOutput("Tree_Fig"), type = 6),
height = "auto",
width = "auto"
),
tabPanel("Accuracy Metrics",
fluidRow(
column(
width = 7,
box(
title = tags$b("ROC Curve"),
solidHeader = TRUE,
withSpinner(plotOutput("Tree_roc"), type = 6),
height = "auto",
width = "auto"
)
),
column(
width = 5,
box(
title = tags$b("Accuracy of the Model - Training Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("dt_acc_train"), type = 1),
height = "auto",
width = "auto"
),
box(
title = tags$b("Accuracy of the Model - Testing Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("dt_acc_test"), type = 1),
height = "auto",
width = "auto"
)
)
))
)),
tabItem(tabName = "lr_widget",
h2(
tags$b("Logistic Regression Accuracy Metrics")
),
tabBox(
width = 12,
tabPanel("Accuracy Metrics",
fluidRow(
column(
width = 7,
box(
title = tags$b("ROC Curve"),
solidHeader = TRUE,
withSpinner(plotOutput("lr_roc"), type = 6),
height = "auto",
width = "auto"
)
),
column(
width = 5,
box(
title = tags$b("Accuracy of the Model - Training Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("lr_acc_train"), type = 1),
height = "auto",
width = "auto"
),
box(
title = tags$b("Accuracy of the Model - Testing Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("lr_acc_test"), type = 1),
height = "auto",
width = "auto"
)
)
))
)),
tabItem(tabName = "knn_widget",
h2(
tags$b("KNN Classification Accuracy Metrics")
),
tabBox(
width = 12,
tabPanel("Accuracy Metrics",
fluidRow(
column(
width = 7,
box(
title = tags$b("ROC Curve"),
solidHeader = TRUE,
withSpinner(plotOutput("knn_roc"), type = 6),
height = "auto",
width = "auto"
)
),
column(
width = 5,
box(
title = tags$b("Accuracy of the Model - Training Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("knn_acc_train"), type = 1),
height = "auto",
width = "auto"
),
box(
title = tags$b("Accuracy of the Model - Testing Data"),
solidHeader = TRUE,
withSpinner(verbatimTextOutput("knn_acc_test"), type = 1),
height = "auto",
width = "auto"
)
)
))
)),
tabItem(
tabName = "data_define",
h2(tags$b("Attribute Description")),
box(
width = 12,
style = "font-size: 150%",
tags$b("Age: "),
br(),
"Age of the cutomer",
br(),
br(),
tags$b("Job: "),
br(),
(
"Type of job - admin., bluecollar, entrepreneur, housemaid, management, retired, selfemployed,
services, student, technician, unemployed, unknown"
),
br(),
br(),
tags$b("Martial: "),
br(),
("Martial status - divorced, married, single, unknown"),
br(),
br(),
tags$b("Education: "),
br(),
(
" Maximum level of education - basic.4y , basic.6y , basic.9y , high.school ,
illiterate , professional.course , university.degree , unknown"
),
br(),
br(),
tags$b("Default Credit: "),
br(),
("Has credit in default? - no, yes, unknown"),
br(),
br(),
tags$b("Contact: "),
br(),
("Contact communication type - cellular, telephone"),
br(),
br(),
tags$b("Month: "),
br(),
(
"Last contact month of the year - jan, feb, mar, apr, may, june, july, aug, sep, oct,
nov, dec"
),
br(),
br(),
tags$b("Day of Week: "),
br(),
("Last contact day of the week - mon, tue, wed, thu, fri"),
br(),
br(),
tags$b("Campaign: "),
br(),
(
"Number of contacts performed during this campaign and for this client"
),
br(),
br(),
tags$b("Previous: "),
br(),
(
"Number of contacts performed before this campaign and for this client"
),
br(),
br(),
tags$b("Poutcome: "),
br(),
(
"Outcome of the previous marketing campaign - failure, nonexistent, success"
),
br(),
br(),
tags$b("Emp var rate: "),
br(),
("Employmet variation rate - quarterly indicator"),
br(),
br(),
tags$b("Cons price index: "),
br(),
("Consumer Price Index - monthly indicator"),
br(),
br(),
tags$b("euribor3m: "),
br(),
("Euribor 3 month rate - daily indicator"),
br(),
br(),
tags$b("nr_employed: "),
br(),
("Number of employees - quarterly indicator"),
br()
)
),
tabItem(
tabName = "glossary",
h2(tags$b("Accuracy metrices term descriptions")),
box(
width = 12,
style = "font-size: 150%",
tags$b("Precision: "),
br(),
"Precision tells us about when",
tags$em("it predicts Yes, how often is it correct."),
br(),
br(),
tags$b("Recall: "),
br(),
"Recall gives us an idea about when",
tags$em("it is actually Yes, how often does it predict Yes."),
br(),
br(),
tags$b("Sensitivity: "),
br(),
"Ability of the test to correctly identify the",
tags$em("true positive rate."),
br(),
br(),
tags$b("Specificity: "),
br(),
"Ability of the test to correctly identify the",
tags$em("true negative rate."),
br()
)
),
tabItem(tabName = "data_example",
h2(tags$b(
"Example datasets for reference"
)),
tabBox(
width = 12,
tabPanel(
title = tags$b("Ideal Customers") ,
solidHeader = TRUE,
withSpinner(DT::dataTableOutput("best_10_lr"), type = 1),
height = "auto",
width = "auto"
),
tabPanel(
title = tags$b("Non-Ideal Customers") ,
solidHeader = TRUE,
withSpinner(DT::dataTableOutput("worst_10_lr"), type = 1),
height = "auto",
width = "auto"
)
))
)
))
)