The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

mltest 1.0.1

• 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”)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.