calculate_variable_split: Internal Function for Split Points for Selected Variables

In ModelOriented/ingredients: Effects and Importances of Model Ingredients

Internal Function for Split Points for Selected Variables

Description

This function calculate candidate splits for each selected variable. For numerical variables splits are calculated as percentiles (in general uniform quantiles of the length grid_points). For all other variables splits are calculated as unique values.

Usage

calculate_variable_split(
  data,
  variables = colnames(data),
  grid_points = 101,
  variable_splits_type = "quantiles",
  new_observation = NA
)

## Default S3 method:
calculate_variable_split(
  data,
  variables = colnames(data),
  grid_points = 101,
  variable_splits_type = "quantiles",
  new_observation = NA
)

Arguments

data	validation dataset. Is used to determine distribution of observations.
variables	names of variables for which splits shall be calculated
grid_points	number of points used for response path
variable_splits_type	how variable grids shall be calculated? Use "quantiles" (default) for percentiles or "uniform" to get uniform grid of points
new_observation	if specified (not NA) then all values in new_observation will be included in variable_splits

Details

Note that calculate_variable_split function is S3 generic. If you want to work on non standard data sources (like H2O ddf, external databases) you should overload it.

Value

A named list with splits for selected variables

ModelOriented/ingredients documentation built on March 16, 2023, 1:53 a.m.