score {SLOPE} | R Documentation |
Compute one of several loss metrics on a new data set
Description
This function is a unified interface to return various types of loss for a
model fit with SLOPE()
.
Usage
score(object, x, y, measure)
## S3 method for class 'GaussianSLOPE'
score(object, x, y, measure = c("mse", "mae"))
## S3 method for class 'BinomialSLOPE'
score(object, x, y, measure = c("mse", "mae", "deviance", "misclass", "auc"))
## S3 method for class 'MultinomialSLOPE'
score(object, x, y, measure = c("mse", "mae", "deviance", "misclass"))
## S3 method for class 'PoissonSLOPE'
score(object, x, y, measure = c("mse", "mae"))
Arguments
object |
an object of class |
x |
feature matrix |
y |
response |
measure |
type of target measure. |
Value
The measure along the regularization path depending on the
value in measure
.#'
See Also
Other SLOPE-methods:
coef.SLOPE()
,
deviance.SLOPE()
,
plot.SLOPE()
,
predict.SLOPE()
,
print.SLOPE()
Examples
x <- subset(infert, select = c("induced", "age", "pooled.stratum"))
y <- infert$case
fit <- SLOPE(x, y, family = "binomial")
score(fit, x, y, measure = "auc")
[Package SLOPE version 0.5.1 Index]