MachineShop (version 3.7.0)

summary: Model Performance Summaries

Description

Summary statistics for resampled model performance metrics.

Usage

# 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, ...)

Value

An object of summmary statistics.

Arguments

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 unMLModelFit(object) be passed to summary ("default"), glance, or tidy.

stat

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.

Examples

# \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)
# }