This function is a unified interface to return various types of loss for a
model fit with SLOPE()
.
score(object, x, y, measure)
# S3 method for GaussianSLOPE
score(object, x, y, measure = c("mse", "mae"))
# S3 method for BinomialSLOPE
score(object, x, y, measure = c("mse", "mae", "deviance", "misclass", "auc"))
# S3 method for MultinomialSLOPE
score(object, x, y, measure = c("mse", "mae", "deviance", "misclass"))
# S3 method for PoissonSLOPE
score(object, x, y, measure = c("mse", "mae"))
an object of class "SLOPE"
feature matrix
response
type of target measure. "mse"
returns mean squared error.
"mae"
returns mean absolute error, "misclass"
returns
misclassification rate, and "auc"
returns area under the ROC curve.
The measure along the regularization path depending on the
value in measure
.#'
Other SLOPE-methods:
coef.SLOPE()
,
deviance.SLOPE()
,
plot.SLOPE()
,
predict.SLOPE()
,
print.SLOPE()