#' OpenMLTaskResults
#'
#' @title Construct OpenMLTaskResults.
#'
#' @description Objects of this class are returned by \code{\link{downloadOpenMLTaskResults}}. All
#' members are filled in by the server.
#'
#' @param task.id [\code{integer(1)}]\cr
#' ID of the OpenML task.
#' @param task.name [\code{character(1)}]\cr
#' A name describing the task shortly.
#' @param task.type.id [\code{integer(1)}]\cr
#' ID of the task type.
#' @param input.data [\code{integer(1)}]\cr
#' ID of the data set that belongs to the task.
#' @param estimation.procedure [\code{character(1)}]\cr
#' The task's estimation procedure.
#' @param metrics [\code{data.frame}]\cr
#' A data.frame of the metrics of all runs that were uploaded for this task.
#' @export
#' @aliases OpenMLTaskResults
#' @seealso \code{\link{downloadOpenMLTaskResults}}
makeOpenMLTaskResults = function(task.id, task.name, task.type.id = NA_integer_,
input.data = NA_integer_, estimation.procedure = NA_character_, metrics) {
assertCount(task.id)
assertString(task.name)
assertCount(task.type.id, na.ok = TRUE)
assertCount(input.data, na.ok = TRUE)
assertString(estimation.procedure, na.ok = TRUE)
assertDataFrame(metrics)
makeS3Obj("OpenMLTaskResults",
task.id = task.id,
task.name = task.name,
task.type.id = task.type.id,
input.data = input.data,
estimation.procedure = estimation.procedure,
metrics = metrics
)
}
# ***** Methods *****
# show
#' @export
print.OpenMLTaskResults = function(x, print.metrics = FALSE, ...) {
catNotNA = function(s, val) {
if (!is.na(val))
catf("%s %s", s, val)
}
## General info
catf('\nTask Results :: (Task ID = %i, Data ID = %i)', x$task.id, x$input.data)
catNotNA('\tTask Type ID : ', x$task.type.id)
catNotNA('\tEstimation Procedure: ', x$estimation.procedure)
if (print.metrics) {
cat('\n\tMetrics :\n\n')
print(x$metrics[, colnames(x$metrics) %nin% c("confusion_matrix", "os_information")])
}
}
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