Nothing
conf_result <- eventReactive(input$submit_conf, {
if (input$conf_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$conf_fmla, data = data, family = binomial(link = "logit"))
}
if (input$conf_use_test_data) {
out <- blr_confusion_matrix(k, cutoff = input$conf_cutoff, data = final_split$test)
} else {
out <- blr_confusion_matrix(k, cutoff = input$conf_cutoff, data = final_split$train)
}
return(out)
})
confusion_title <- eventReactive(input$submit_conf, {
column(12, align = 'center', h4('Confusion Matrix & Model Performance Measures'))
})
output$conf_title <- renderUI({
confusion_title()
})
output$conf_out <- renderPrint({
conf_result()
})
# hosmer lemeshow test
hoslem_result <- eventReactive(input$submit_hoslem, {
if (input$hoslem_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$hoslem_fmla, data = data, family = binomial(link = "logit"))
}
if (input$hoslem_use_test_data) {
out <- blr_test_hosmer_lemeshow(k, data = final_split$test)
} else {
out <- blr_test_hosmer_lemeshow(k, data = final_split$train)
}
return(out)
})
output$hoslem_out <- renderPrint({
hoslem_result()
})
# gains chart and roc curve
lift_result <- eventReactive(input$submit_lift, {
if (input$lift_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$lift_fmla, data = data, family = binomial(link = "logit"))
}
if (input$lift_use_test_data) {
out <- blr_gains_table(k, data = final_split$test)
} else {
out <- blr_gains_table(k, data = final_split$train)
}
return(out)
})
gains_title <- eventReactive(input$submit_lift, {
column(12, align = 'center', h4('Gains Table & Lift Chart'))
})
output$lift_title <- renderUI({
gains_title()
})
output$gains_table_out <- renderPrint({
lift_result()
})
output$lift_out <- renderPlot({
plot(lift_result())
})
# ROC curve
roc_result <- eventReactive(input$submit_roc, {
if (input$roc_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$roc_fmla, data = data, family = binomial(link = "logit"))
}
if (input$roc_use_test_data) {
out <- blr_gains_table(k, data = final_split$test)
} else {
out <- blr_gains_table(k, data = final_split$train)
}
return(out)
})
output$roc_out <- renderPlot({
blr_roc_curve(roc_result())
})
# KS chart
ks_result <- eventReactive(input$submit_ks, {
if (input$ks_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$ks_fmla, data = data, family = binomial(link = "logit"))
}
if (input$ks_use_test_data) {
out <- blr_gains_table(k, data = final_split$test)
} else {
out <- blr_gains_table(k, data = final_split$train)
}
return(out)
})
output$ks_out <- renderPlot({
blr_ks_chart(ks_result())
})
# lorenz curve
lorenz_result <- eventReactive(input$submit_lorenz, {
if (input$lorenz_use_prev) {
k <- model()
} else {
data <- final_split$train
k <- glm(input$lorenz_fmla, data = data, family = binomial(link = "logit"))
}
return(k)
})
output$lorenz_out <- renderPlot({
blorr::blr_lorenz_curve(lorenz_result())
})
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.