vip: gen_friedman – R documentation

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vip

gen_friedman

Friedman benchmark data

Description

Simulate data from the Friedman 1 benchmark problem. See mlbench.friedman1 for details and references.

Usage

gen_friedman(
  n_samples = 100,
  n_features = 10,
  n_bins = NULL,
  sigma = 0.1,
  seed = NULL
)

Arguments

`n_samples`	Integer specifying the number of samples (i.e., rows) to generate. Default is 100.
`n_features`	Integer specifying the number of features to generate. Default is 10.
`n_bins`	Integer specifying the number of (roughly) equal sized bins to split the response into. Default is `NULL` for no binning. Setting to a positive integer > 1 effectively turns this into a classification problem where `n_bins` gives the number of classes.
`sigma`	Numeric specifying the standard deviation of the noise.
`seed`	Integer specifying the random seed. If `NULL` (the default) the results will be different each time the function is run.

Note

This function is mostly used for internal testing.

Examples

gen_friedman()

vip

Variable Importance Plots

v0.3.2

GPL (>= 2)

Authors

Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>), Brad Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Bernie Gray [aut] (<https://orcid.org/0000-0001-9190-6032>)

Initial release