Attribute-based criterion templates

Criterion constructors for case-level attributes, covering the common measurement scales. Each builds a measure from a named attribute of the traces object.

Usage

crit_nominal(attribute, weight = 1, name = attribute)

crit_ordinal(
  attribute,
  levels,
  weight = 1,
  indifference = as_quantile(0.5),
  similarity = as_quantile(0.2),
  veto = NULL,
  name = attribute
)

crit_numeric(
  attribute,
  weight = 1,
  transform = identity,
  indifference = as_quantile(0.5),
  similarity = as_quantile(0.2),
  veto = NULL,
  name = attribute
)

Arguments

attribute

Name of a case attribute carried by the traces object.

weight

A single positive weight.

name

Criterion label; defaults to the attribute name.

levels

For crit_ordinal(), the attribute values from lowest to highest rank.

indifference, similarity, veto

Thresholds; a number or an as_quantile() specification. Defaults suit the direction and are overridable.

transform

For crit_numeric(), a function applied to the numeric attribute before differencing (e.g. log); defaults to identity().

Value

A criterion() object.

Details

• crit_nominal() scores a pair 1 when the attribute is equal and 0 otherwise (similarity direction; thresholds preset, no veto).

• crit_ordinal() uses the absolute rank difference |rank_a - rank_b| over the ordered levels (dissimilarity direction); it covers Likert scales.

• crit_numeric() uses |x_a - x_b| after an optional transform (dissimilarity direction); it covers quantitative, interval and percentage scales.

See also

crit_activity_profile() and the other process-aware helpers.

Examples

crit_nominal("status", weight = 0.3)
#> <criterion 'status'>: direction = similarity, weight = 0.3
#>   indifference = 0, similarity = 1, veto = none
crit_ordinal("triage", levels = c("green", "yellow", "red"), weight = 0.2)
#> <criterion 'triage'>: direction = dissimilarity, weight = 0.2
#>   indifference = as_quantile(0.5), similarity = as_quantile(0.2), veto = none
crit_numeric("age", weight = 0.2, transform = identity)
#> <criterion 'age'>: direction = dissimilarity, weight = 0.2
#>   indifference = as_quantile(0.5), similarity = as_quantile(0.2), veto = none