Xy: Xy

In andrebleier/Xy: Simulating Supervised Learning Data

Xy

Description

The Xy function invokes a framework to simulate supervised learning tasks. With this function you can specify the learning task (regression or classification) and you can adjust specifics such as link functions and cutoff values (e.g. for classification). The outcoming object serves as a mere simulation recipe and has to be enhanced by functions which add effects to the simulation (see add_effects). Once you have specified the recipe, you can cook the recipe with the simulate() method.

Usage

Xy(task = "regression", link = NULL, cutoff = NULL)

Arguments

task	a character specifying the supervised learning task (e.g. "regression" or "classification").
link	a link function to be used to transform the target.
cutoff	a cutoff function. This function is applied after the link function.

Value

Returns an object of class xy_recipe. It is a simulation recipe. which has to be cooked with simulate() to render a simulation.

Author(s)

Andre Bleier ([e-mail])

Examples

# create a recipe
recipe <- Xy() %>%
  add_linear(p = 5, family = xy_normal())

andrebleier/Xy documentation built on March 29, 2023, 12:41 p.m.