Changes in version 1.0.3 (2025-02-03)                  

  - added CRAN-assigned DOI to the inst/CITATION file
  - removed balanced.accuracy mentioned twice in the #' @description
  - removed 2nd parenthesis pair around ((\strong{FOR})) in the .R file
  - replaced \emph{calculated as:} with = in the #' @return of the .R
    file
  - removed redundant parentheses in \item{F0.5}, \item{1} and \item{F2}

                 Changes in version 1.0.2 (2025-02-02)                  

  - \strong{} removed from within the the \item{} of the return in the
    #' @return part of the roxygen2 header
      - thanks to Dr. Hornik for the advice
  - \bugfix: TN is now caclulated correctly (#107): TN <-
    sapply(1:length(TP), function(y) {sum(confusion_mtx[-y, -y], na.rm =
    TRUE)})
      - thanks to Dr. Stewart for the advice
  - ORCID number is added in the description file

                 Changes in version 1.0.1 (2018-11-16)                  

  - added bibliography in the help page of the function
    "mltest::ml_test()"
  - removed "mltest.R" file which previously described the package
  - redone/simplified the implementation of the calculation of local
    variables "TP" and "TN"
    within "mltest::ml_test()"
  - added variables "FP" and "FN" (semantiaclly corresponding to FP and
    FN of a confusion matrix) within "mltest::ml_test()"
  - reimplemented/expressed evaluation-metrics "precision", "recall",
    "specificity" in simple
    terms of TP, TN, FP and FN
  - implemented new evaluation-metrics: "DOR", "error.rate",
    "FDR"/"FNR"/"FOR"/"FPR", "geometric.mean", "Jaccard", "L"/"lambda"
    (representing LR(+) and LR(-) respectively), "MCC", "MK"
    (Markedness), "NPV", "OP" (optimization precision), "Youden"('s
    index)
  - added an extra argument "output.as.table" which is FALSE by default:
    this returns a list with named vectors (class-mtrics) for fast
    access through referencing/subsetting a la $. when the above
    "output.as.table" = TRUE the dataframe with all the metrics is
    returned (except for "accuracy" and "error.rate")