summary | R Documentation |
Summary statistics for resampled model performance metrics.
## S3 method for class 'ConfusionList'
summary(object, ...)
## S3 method for class 'ConfusionMatrix'
summary(object, ...)
## S3 method for class 'MLModel'
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
## S3 method for class 'MLModelFit'
summary(object, .type = c("default", "glance", "tidy"), ...)
## S3 method for class 'Performance'
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
## S3 method for class 'PerformanceCurve'
summary(object, stat = MachineShop::settings("stat.Curve"), ...)
## S3 method for class 'Resample'
summary(
object,
stats = MachineShop::settings("stats.Resample"),
na.rm = TRUE,
...
)
## S3 method for class 'TrainingStep'
summary(object, ...)
object |
confusion, lift, trained model fit, performance, performance curve, resample, or rfe result. |
... |
arguments passed to other methods. |
stats |
function, function name, or vector of these with which to compute summary statistics. |
na.rm |
logical indicating whether to exclude missing values. |
.type |
character string specifying that
|
stat |
function or character string naming a function to compute a
summary statistic at each cutoff value of resampled metrics in
|
An object of summmary statistics.
## 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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