
Summary statistics for resampled model performance metrics.
# S3 method for ConfusionList
summary(object, ...)# S3 method for ConfusionMatrix
summary(object, ...)
# S3 method for MLModel
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
# S3 method for MLModelFit
summary(object, .type = c("default", "glance", "tidy"), ...)
# S3 method for Performance
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
# S3 method for PerformanceCurve
summary(object, stat = MachineShop::settings("stat.Curve"), ...)
# S3 method for Resample
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
# S3 method for TrainingStep
summary(object, ...)
An object of summmary statistics.
confusion, lift, trained model fit, performance, performance curve, resample, or rfe result.
arguments passed to other methods.
function, function name, or vector of these with which to compute summary statistics.
logical indicating whether to exclude missing values.
character string specifying that
unMLModelFit(object)
be passed to
summary
("default"
),
glance
, or
tidy
.
function or character string naming a function to compute a
summary statistic at each cutoff value of resampled metrics in
PerformanceCurve
, or NULL
for resample-specific metrics.
# \donttest{
## Requires prior installation of suggested package gbm to run
## Factor response example
fo <- Species ~ .
control <- CVControl()
gbm_res1 <- resample(fo, iris, GBMModel(n.trees = 25), control)
gbm_res2 <- resample(fo, iris, GBMModel(n.trees = 50), control)
gbm_res3 <- resample(fo, iris, GBMModel(n.trees = 100), control)
summary(gbm_res3)
res <- c(GBM1 = gbm_res1, GBM2 = gbm_res2, GBM3 = gbm_res3)
summary(res)
# }
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