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Dials for ordinalForest engine parameters

Source: R/param-engine-ordinalForest.R
ordinalForest_parameters.Rd

These parameters are auxiliary to random forest models that use the "ordinalForest" engine. They correspond to tuning parameters that would be specified using set_engine("ordinalForest", ...).

Usage

naive_scores(values = c(FALSE, TRUE))

num_scores(range = c(100L, 2000L), trans = NULL)

num_score_perms(range = c(100L, 500L), trans = NULL)

num_score_trees(range = c(10L, 200L), trans = NULL)

num_scores_best(range = c(2L, 20L), trans = NULL)

ord_metric(values = values_ord_metric)

values_ord_metric

Format

An object of class character of length 4.

Arguments

values

A character string of possible values. See values_ord_metric.

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.

Value

An object of S3 parent class param and primary class qual_param or quant_param; see dials::new_qual_param() and [dials::new_quant_param().

Details

These functions generate parameters for parsnip::rand_forest() models using the "ordinalForest" engine. See ?ordinalForest::ordfor() for more details on the original parameters. These parameters are engine-specific, not general to decision tree models, so are provided here rather than in dials.

  • naive_scores(): Whether to construct only a "naive" ordinal forest using the scores \(1,2,3,\ldots\) for the ordinal values; tunes naive.

  • num_scores(): The number of score sets tried prior to optimization; tunes nsets.

  • num_score_perms(): The number of permutations of the class width ordering to try for each score set tried (after the first); tunes npermtrial.

  • num_score_trees(): The number of trees in the score set–specific forests; tunes ntreeperdiv.

  • num_scores_best(): The number of top-performing score sets used to calculate the optimized score set; tunes nbest.

  • ord_metric(): The performance function used to evaluate score set–specific forests; tunes perffunction. See also ?ordinalForest::perff.

See also

dials::trees()

Examples

naive_scores()
#> Use Naive Ordinal Scores? (qualitative)
#> 2 possible values include:
#> FALSE and TRUE
num_scores()
#> # Score Sets Tried (quantitative)
#> Range: [100, 2000]
num_score_perms()
#> # Class Width Permutations (quantitative)
#> Range: [100, 500]
num_score_trees()
#> # Trees per Score Set (quantitative)
#> Range: [10, 200]
num_scores_best()
#> # Top Score Sets (quantitative)
#> Range: [2, 20]
ord_metric()
#> Ordinal Performance Function (qualitative)
#> 4 possible values include:
#> 'equal', 'probability', 'proportional', and 'oneclass'