ppv | R Documentation |
Measure to compare true observed labels with predicted labels in binary classification tasks.
ppv(truth, response, positive, na_value = NaN, ...) precision(truth, response, positive, na_value = NaN, ...)
truth |
( |
response |
( |
positive |
( |
na_value |
( |
... |
( |
The Positive Predictive Value is defined as
TP / (TP + FP).
Also know as "precision".
This measure is undefined if TP + FP = 0.
Performance value as numeric(1)
.
Type: "binary"
Range: [0, 1]
Minimize: FALSE
Required prediction: response
https://en.wikipedia.org/wiki/Template:DiagnosticTesting_Diagram
Goutte C, Gaussier E (2005). “A Probabilistic Interpretation of Precision, Recall and F-Score, with Implication for Evaluation.” In Lecture Notes in Computer Science, 345–359. doi: 10.1007/978-3-540-31865-1_25.
Other Binary Classification Measures:
auc()
,
bbrier()
,
dor()
,
fbeta()
,
fdr()
,
fnr()
,
fn()
,
fomr()
,
fpr()
,
fp()
,
mcc()
,
npv()
,
prauc()
,
tnr()
,
tn()
,
tpr()
,
tp()
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) ppv(truth, response, positive = "a")
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