NEWS.md

In mltest: Classification Evaluation Metrics

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")

mltest documentation built on May 2, 2019, 7:26 a.m.