Create a governed classification decision rule

Usage

create_gazepoint_decision_rule(
  metric,
  direction = c("maximize", "minimize"),
  threshold = NULL,
  threshold_origin = c("predeclared", "training", "inner_resampling"),
  cost_false_positive = 1,
  cost_false_negative = 1,
  abstention_allowed = FALSE,
  abstention_interval = NULL,
  calibration_source = "none",
  training_partition = "analysis",
  generalization_target,
  scientific_justification
)

Arguments

metric: Metric used to justify the threshold.
direction: Either "maximize" or "minimize".
threshold: Optional probability threshold. Leave NULL until selected.
threshold_origin: Origin of the threshold.
cost_false_positive: Non-negative false-positive cost.
cost_false_negative: Non-negative false-negative cost.
abstention_allowed: Whether abstention is permitted.
abstention_interval: Optional length-two probability interval. Probabilities inside the interval are labelled as abstentions.
calibration_source: Description of the calibration source.
training_partition: Description of the data partition used to determine the threshold.
generalization_target: Declared generalization target.
scientific_justification: Explicit scientific justification.

Value

A gp3ml_decision_rule.