--- a
+++ b/R/J48DTeval.R
@@ -0,0 +1,50 @@
+#' @title Evaluating the performance of the J48 decision tree.
+#' @description This function evaluates the performance of the generated trees
+#'   for error estimation by ten-fold cross validation assessment.
+#' @export
+#' @param data The resulted data from running the function J48DT.
+#' @param num.folds A numeric value of the number of folds for the cross
+#'   validation assessment. Default is 10.
+#' @param First A string vector showing the first target cluster.  Default is
+#'   "CL1"
+#' @param Second A string vector showing the second target cluster.  Default is
+#'   "CL2"
+#' @param quiet If `TRUE`, suppresses intermediary output
+#' @importFrom stats predict
+#' @return Statistics about the J48 model
+J48DTeval <- function(
+  data, num.folds = 10, First = "CL1", Second = "CL2", quiet = FALSE
+) {
+  exp.imput.df <- as.data.frame(t(data))
+  num.instances <- nrow(exp.imput.df)
+  indices <- 1:num.instances
+  classVector <- factor(colnames(data))
+  cv.segments <- split(
+    sample(indices), rep(1:num.folds, length = num.instances)
+  )
+  j48.performance <- cross.val(
+    exp.imput.df, classVector, cv.segments, j48.performance, "J48", quiet
+  )
+  if (!quiet) print(j48.performance)
+
+  j48.confusion.matrix <- matrix(j48.performance, nrow = 2)
+  rownames(j48.confusion.matrix) <- c(
+    paste0("Predicted", First), paste0("Predicted", Second)
+  )
+  colnames(j48.confusion.matrix) <- c(First, Second)
+  if (!quiet) print(j48.confusion.matrix)
+  j48.sn <- round(SN(j48.confusion.matrix), digits = 2)
+  j48.sp <- round(SP(j48.confusion.matrix), digits = 2)
+  j48.acc <- round(ACC(j48.confusion.matrix), digits = 2)
+  j48.mcc <- round(MCC(j48.confusion.matrix), digits = 2)
+
+  if (!quiet) {
+    message(
+      "J48 SN: ", j48.sn, "\n",
+      "J48 SP: ", j48.sp, "\n",
+      "J48 ACC: ", j48.acc, "\n",
+      "J48 MCC: ", j48.mcc, "\n"
+    )
+  }
+  return(j48.performance)
+}