evaluate-methods: Methods for cross-validation results.

In funcml: Functional Machine Learning Framework

Methods for cross-validation results.

Description

These methods provide the standard print() and summary() interfaces for funcml_eval objects, plus a plot() method for fold-level diagnostics.

Usage

## S3 method for class 'funcml_eval'
print(x, digits = 4L, ...)

## S3 method for class 'funcml_eval'
summary(object, digits = 4L, ...)

## S3 method for class 'funcml_eval'
plot(x, ...)

Arguments

x	A funcml_eval object.
digits	Number of digits numeric columns are rounded to when printed.
...	Additional arguments passed to the underlying method.
object	A funcml_eval object.

Value

print() and summary() return the input object or summary table invisibly. plot() returns a ggplot2 object.

Examples

eval_obj <- evaluate(
  data = mtcars,
  formula = mpg ~ wt + hp,
  model = "glm",
  resampling = cv(3, seed = 1),
  metrics = c("rmse", "mae")
)
print(eval_obj)
summary(eval_obj)
plot(eval_obj)

funcml documentation built on Aug. 22, 2026, 5:08 p.m.