Forgot to load package caret.

R/explore_plot.R

@@ -47,7 +47,7 @@ plot_server <- function(input, output, session, rv) {
         coord_cartesian(expand = TRUE)
       if(!is.null(rv$clusters)) {
         idx.to.na <- which(clusters == "")
-        if(length(idx.to.na)>0) { 
+        if(length(idx.to.na)>0) {
           clusters[idx.to.na] <- NA
         }
         p <- p + geom_point(aes(colour = factor(clusters[1:nrow(D)])), alpha = 0.5) +

R/feature_selection.R

 # Authors: Jean-Karim Heriche
 
-#TODO
-
 ##############################
 ## Feature selection Module ##
 ##############################
@@ -217,9 +215,13 @@ feature_selection_server  <- function(input, output, session, rv, session_parent
       }
       tmp <- rv$data[,input$featuresToProcess]
       idx.valid.data <- which(is.finite(rowSums(tmp)))
-      preds <- predict(classifier.data$model, newdata = tmp[idx.valid.data,])
-      rv$data[idx.valid.data,]$xgboost.predictions <- classifier.data$classes[preds]
-      showNotification("Model predictions have been added to the data.", type = "warning")
+      if(length(idx.valid.data)>0) {
+        preds <- predict(classifier.data$model, newdata = tmp[idx.valid.data,])
+        rv$data[idx.valid.data,]$xgboost.predictions <- classifier.data$classes[preds]
+        showNotification("Model predictions have been added to the data.", type = "warning")
+      } else {
+        showNotification("Invalid data.", type = "error")
+      }
     }
   })
   

image_data_explorer.R

@@ -51,6 +51,7 @@ library(RANN)
 library(MASS)
 library(uwot)
 library(xgboost)
+library(caret)
 
 ## Making data table filtering persistent
 ## from https://dev.to/awwsmm/reactive-datatables-in-r-with-persistent-filters-l26