accuracy: Compute predictive accuracy.
In dplbnDE: Discriminative Parameter Learning of Bayesian Networks by Differential Evolution
accuracy R Documentation
Compute predictive accuracy.
Description
Compute predictive accuracy.
Usage
accuracy(x, y)
Arguments
x
A vector of predicted labels.
y
A vector of true labels.
Examples
data(car)
dpl.lshade <- lshade(NP = 20, G = 25, data = car, class.name = names(car)[7], c = 0.1,
structure = "tan", pB = 0.05, edgelist = NULL, verbose = 5)
p <- predict(dpl.lshade$Best, car)
accuracy(p, car$class)
dplbnDE documentation built on Aug. 19, 2023, 1:07 a.m.
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| accuracy | R Documentation |
Compute predictive accuracy.
Description
Compute predictive accuracy.
Usage
accuracy(x, y)
Arguments
x |
A vector of predicted labels. |
y |
A vector of true labels. |
Examples
data(car)
dpl.lshade <- lshade(NP = 20, G = 25, data = car, class.name = names(car)[7], c = 0.1,
structure = "tan", pB = 0.05, edgelist = NULL, verbose = 5)
p <- predict(dpl.lshade$Best, car)
accuracy(p, car$class)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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