interpret-pdp-methods: Partial dependence result methods.

In funcml: Functional Machine Learning Framework

Partial dependence result methods.

Description

These methods provide the standard print(), summary(), and plot() interfaces for funcml_pdp objects returned by interpret(method = "pdp").

Usage

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

## S3 method for class 'funcml_pdp'
print(x, ...)

## S3 method for class 'funcml_pdp'
summary(object, ...)

Arguments

x	A funcml_pdp object.
...	Additional arguments passed to the underlying method.
object	A funcml_pdp object.

Value

plot() returns a ggplot2 object. print() returns the input object invisibly. summary() returns the partial dependence table invisibly.

Examples

fit_obj <- fit(mpg ~ wt + hp + disp, data = mtcars, model = "rpart",
  spec = list(cp = 0.01, minsplit = 5))
pdp <- interpret(
  fit = fit_obj,
  data = mtcars,
  method = "pdp",
  features = c("wt", "hp"),
  nsamples = 20
)
print(pdp)
summary(pdp)
plot(pdp)

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