Title

Title

new_score_obj(
  subclass = c("cat_num", "cat_cat", "num_num", "any"),
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = NULL,
  range = NULL,
  inclusive = NULL,
  fallback_value = NULL,
  score_type = NULL,
  trans = NULL,
  sorts = NULL,
  direction = NULL,
  deterministic = NULL,
  tuning = NULL,
  ties = NULL,
  calculating_fn = NULL,
  label = NULL,
  ...
)

Arguments

subclass

A character string.

outcome_type

A character string. One of:

• "numeric"

• "factor"

predictor_type

A character string. One of:

• "numeric"

• "factor"

case_weights

NULL

range

A numeric vector of length two, specifying the minimum and maximum possible values, respectively.

inclusive

A logical vector of length two, indicating whether the lower and upper bounds of the range are inclusive (TRUE) or exclusive (FALSE), respectively.

fallback_value

A numeric scalar used as a fallback value. Typical values include: 0, 1, or Inf.

score_type

A character string.

trans

A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). Or use built-in functions, such as transform_abs() or transform_neg_log10(). Create custom transforms with scales::trans_new().

sorts

NULL

direction

A character string. One of:

• "maximize"

• "minimize"

• "target"

deterministic

A logical value, indicating whether the resulting score is deterministic (TRUE) or random (FALSE).

tuning

A logical value, indicating whether the model should be tuned (TRUE) or not (FALSE).

ties

A logical value indicating whether ties in score can occur (TRUE) or not (FALSE).

calculating_fn

NULL

label

NULL

...

NULL

Examples

NULL
#> NULL