Amount of supervision parameter — target

For uwot::umap() and embed::step_umap(), this is a weighting factor between data topology and target topology. A value of 0.0 weights entirely on data, a value of 1.0 weights entirely on target. The default of 0.5 balances the weighting equally between data and target.

Usage

target_weight(range = c(0, 1), trans = NULL)

Arguments

range: A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.
trans: A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

Details

This parameter is used in recipes via embed::step_umap().

Examples

target_weight()
#> Proportion Supervised (quantitative)
#> Range: [0, 1)