Score Estimate — mean_score • renoir

Computes a score estimate given different sets of data

Usage

mean_score(scorer, true, pred, weights, ...)

# S4 method for Scorer,list,list
mean_score(
  scorer,
  true,
  pred,
  weights = NULL,
  multi = c("average", "sum"),
  grouped = TRUE,
  min.obs = 3,
  logger,
  ...
)

# S4 method for ScorerList,list,list
mean_score(
  scorer,
  true,
  pred,
  weights = NULL,
  multi = c("average", "sum"),
  grouped = TRUE,
  logger,
  ...
)

Arguments

scorer

a ScorerList object

true

a list of vectors (or matrices) of observed values. If list elements are matrices, a multi-response is assumed

pred

a list of vectors (or matrices) of predicted values

weights

a list of vectors of observation weights

...

further arguments to scorer function

multi

what to do when response has multiple output values

average: errors of multiple outputs are averaged to get a single value for each observation
sum: errors of multiple outputs are summed up to get a single value for each observation

grouped

logical, whether to compute separate statistics when lists of values are provided

min.obs

integer, minimum number of observations per list. If the number of observations per list is less than min.obs, an attempt to compute errors at the observation level (for the unlisted observations) and then summarise is made (equivalent to grouped = FALSE). It is working only for certain accuracy measures. Default is min.obs = 3. Set min.obs = 0 to suppress.

logger

a Logger object

Value

the computed score estimate (the average error)

list containing the computed score estimate (the average error) for each Scorer in the ScorerList