MachineShop (version 1.6.0)

summary: Model Performance Summary

Description

Summary statistics for resampled model performance metrics.

Usage

# S3 method for Confusion
summary(object, ...)
# S3 method for ConfusionMatrix
summary(object, ...)
# S3 method for Curves
summary(object,
  stat = MachineShop::settings("stat.Curves"), ...)
# S3 method for MLModelTune
summary(object,
  stats = MachineShop::settings("stats.Resamples"), na.rm = TRUE, ...)
# S3 method for Performance
summary(object,
  stats = MachineShop::settings("stats.Resamples"), na.rm = TRUE, ...)
# S3 method for Resamples
summary(object,
  stats = MachineShop::settings("stats.Resamples"), na.rm = TRUE, ...)

Arguments

object

confusion, performance curve, lift, model tune, performance, or resample result.

...

arguments passed to other methods.

stat

function or character string naming a function to compute a summary statistic at each cutoff value of resampled metrics in Curves, or NULL for resample-specific metrics.

stats

function, function name, or vector of these with which to compute summary statistics.

na.rm

logical indicating whether to exclude missing values.

Value

array with summmary statistics in the second dimension, metrics in the first for single models, and models and metrics in the first and third, respectively, for multiple models.

Examples

# NOT 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 <- Resamples(GBM1 = gbm_res1, GBM2 = gbm_res2, GBM3 = gbm_res3)
summary(res)

# }