mlr3measures (version 0.3.0)

mcc: Matthews Correlation Coefficient

Description

Binary classification measure defined as $$ \frac{\mathrm{TP} \cdot \mathrm{TN} - \mathrm{FP} \cdot \mathrm{FN}}{\sqrt{(\mathrm{TP} + \mathrm{FP}) (\mathrm{TP} + \mathrm{FN}) (\mathrm{TN} + \mathrm{FP}) (\mathrm{TN} + \mathrm{FN})}}. $$

Usage

mcc(truth, response, positive, ...)

Arguments

truth

:: factor() True (observed) labels. Must have the exactly same two levels and the same length as response.

response

:: factor() Predicted response labels. Must have the exactly same two levels and the same length as truth.

positive

:: character(1) Name of the positive class.

...

:: any Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

• Type: "binary"

• Range: \([-1, 1]\)

• Minimize: FALSE

• Required prediction: response

References

Matthews BW (1975). “Comparison of the predicted and observed secondary structure of T4 phage lysozyme.” Biochimica et Biophysica Acta (BBA) - Protein Structure, 405(2), 442--451. 10.1016/0005-2795(75)90109-9.

See Also

Other Binary Classification Measures: auc(), bbrier(), dor(), fbeta(), fdr(), fnr(), fn(), fomr(), fpr(), fp(), npv(), ppv(), prauc(), tnr(), tn(), tpr(), tp()

Examples

# NOT RUN {
set.seed(1)
lvls = c("a", "b")
truth = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
response = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
mcc(truth, response, positive = "a")
# }