General S7 classes for scoring objects

class_score is an S7 object that contains slots for the characteristics of predictor importance scores. More specific classes for individual methods are based on this object (shown below).

Usage

class_score(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame()
)

class_score_aov(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame(),
  neg_log10 = TRUE
)

class_score_cor(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame()
)

class_score_xtab(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame(),
  neg_log10 = TRUE
)

class_score_imp_rf(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame(),
  engine = "ranger"
)

class_score_info_gain(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame(),
  mode = "classification"
)

class_score_roc_auc(
  outcome_type = c("numeric", "factor"),
  predictor_type = c("numeric", "factor"),
  case_weights = logical(0),
  range = integer(0),
  inclusive = logical(0),
  fallback_value = integer(0),
  score_type = character(0),
  sorts = function() NULL,
  direction = character(0),
  deterministic = logical(0),
  tuning = logical(0),
  calculating_fn = function() NULL,
  label = character(0),
  packages = character(0),
  results = data.frame()
)