dependence: Partial Dependence

Description Usage Arguments Value See Also Examples

View source: R/dependence.R

Description

Calculate partial dependence of a response on select predictor variables.

Usage

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dependence(
  object,
  data = NULL,
  select = NULL,
  interaction = FALSE,
  n = 10,
  intervals = c("uniform", "quantile"),
  stats = MachineShop::settings("stats.PartialDependence")
)

Arguments

object

model fit result.

data

data frame containing all predictor variables. If not specified, the training data will be used by default.

select

expression indicating predictor variables for which to compute partial dependence (see subset for syntax) [default: all].

interaction

logical indicating whether to calculate dependence on the interacted predictors.

n

number of predictor values at which to perform calculations.

intervals

character string specifying whether the n values are spaced uniformly ("uniform") or according to variable quantiles ("quantile").

stats

function, function name, or vector of these with which to compute response variable summary statistics over non-selected predictor variables.

Value

PartialDependence class object that inherits from data.frame.

See Also

plot

Examples

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## Requires prior installation of suggested package gbm to run

gbm_fit <- fit(Species ~ ., data = iris, model = GBMModel)
(pd <- dependence(gbm_fit, select = c(Petal.Length, Petal.Width)))
plot(pd)

MachineShop documentation built on June 18, 2021, 9:06 a.m.