mcc {mlr3measures} | R Documentation |
Matthews Correlation Coefficient
Description
Measure to compare true observed labels with predicted labels in binary classification tasks.
Usage
mcc(truth, response, positive, ...)
Arguments
truth |
( |
response |
( |
positive |
( |
... |
( |
Details
The Matthews Correlation Coefficient is 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})}}.
This above formula is undefined if any of the four sums in the denominator is 0. The denominator is then set to 1.
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. doi: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
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")