nds_selection

(<code>matrix()</code>)
Numeric matrix with each column corresponding to a point

points

(<code>integer(1L)</code>)
Amount of points to select.

n_select

(<code>numeric()</code>)
Reference point for hypervolume.

ref_point

('logical()')
Should the ranking be based on minimization?
Can be specified for each dimension or for all.
Default is <code>TRUE</code> for each dimension.

minimize

Select best subset of points by non dominated sorting with
hypervolume contribution for tie breaking. Works on an arbitrary dimension
of size two or higher.

internal

Provides a common framework for optimization of black-box
functions for other packages, e.g. 'mlr3tuning' or 'mlr3fselect'. It
offers various optimization methods e.g. grid search, random search,
generalized simulated annealing and iterated racing.

nds_selection: Best points w.r.t. non dominated sorting with hypervolume contribution.

Description

Usage

Arguments

Value