EvaluateConfigurations: Evaluate candidate configurations on sets of instances
In fcampelo/MetaTuner: MetaTuner: Metaheuristics Tuner

Description Usage Arguments Value Author(s)

Evaluates the candidate configurations listed on configs.to.eval on the tuning instances listed in instances.to.eval. Notice that this routine does not repeat evaluations - if a configuration i already has a performance value for instance j that evaluation is skipped.

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EvaluateConfigurations(tuning.instances, instances.to.eval = "all",
  config.list, configs.to.eval = "all", algo.runner,
  summary.function = "median", parameters)

`tuning.instances`	list containing all available tuning instances.
`instances.to.eval`	vector containing the indices of the instances to be used.
`config.list`	list vector containing field `A` (list of all configurations sampled so far + additional info) as well as other information regarding the performance of all configurations tested and the process of MetaTuner.
`configs.to.eval`	vector containing the indices of the configurations to be evaluated on the instances listed in `instances.to.eval`.
`algo.runner`	name of function used for evaluating the configurations. See Section `Algorithm Runner` of `metatuner()` documentation.
`summary.function`	name of function for aggregating the (scaled) output values of `algo.runner` into a single performance value. Usual functions include `mean` and `median`, but in principle any summarizing function can be used.
`parameters`	data frame containing the parameter names and bound constraints.

Updated config.list containing performance evaluation of configs.to.eval on instances.to.eval, as well as nruns, the number of algorithm runs performed.

Felipe Campelo (fcampelo@ufmg.br), Athila Trindade (rochaathila@gmail.com)

fcampelo/MetaTuner documentation built on May 29, 2019, 9:14 a.m.