Description Usage Arguments Details Value Author(s) See Also Examples
irace
implements iterated Race. It receives some parameters to be tuned
and returns the best configurations found, namely, the elite configurations
obtained from the last iterations (and sorted by rank).
1 | irace(scenario, parameters)
|
scenario |
Data structure containing irace settings.The data structure
has to be the one returned by the function |
parameters |
Data structure containing the parameter definition. The data
structure has to be the one returned by the function |
The function irace
executes the tuning procedure using
the information provided in scenario
and parameters
. Initially it checks
the correctness of scenario
and recovers a previous execution if
scenario$recoveryFile
is set. A R data file log of the execution is created
in scenario$logFile
.
A data frame with the set of best algorithm configurations found by irace. The data frame has the following columns:
.ID.:Internal id of the candidate configuration.
Parameter names: One column per parameter name in parameters
.
.PARENT.: Internal id of the parent candidate configuration.
Additinally, this function saves an R data file containing an object called
iraceResults
. The path of the file is indicated in scenario$logFile
.
The iraceResults
object is a list with the following structure:
scenario: The scenario R object containing the irace options used for the execution. See defaultScenario help for more information.
parameters: The parameters R object containing the description of the target algorithm parameters. See readParameters.
allConfigurations: The target algorithm configurations generated by
irace. This object is a data frame, each row is a candidate configuration,
the first column (.ID.
) indicates the internal identifier of the configuration,
the following columns correspond to the parameter values, each column named as the
parameter name specified in the parameter object. The final column (.PARENT.
)
is the identifier of the configuration from which model the actual configuration
was sampled.
allElites: A list that contains one element per iteration, each element contains
the internal identifier of the elite candidate configurations of the corresponding
iteration (identifiers correspond to allConfigurations$.ID.
).
iterationElites: A vector containing the best candidate configuration internal identifier of each iteration. The best configuration found corresponds to the last one of this vector.
experiments: A matrix with configurations as columns and instances as rows. Column
names correspond to the internal identifier of the configuration (allConfigurations$.ID.
).
experimentLog: A matrix with columns iteration, instance, configuration, time
.
This matrix contains the log of all the experiments that irace performs during its execution.
The instance column refers to the index of the scenario$instancesList
data frame. Time is saved
ONLY when reported by the targetRunner.
softRestart: A logical vector that indicates if a soft restart was performed on each
iteration. If FALSE
, then no soft restart was performed.
state: A list that contains the state of irace, the recovery is done using the information contained in this object.
testing: A list that constains the testing results. The elements of this list are:
experiments
a matrix with the testing expriments of the selected configurations in the
same format as the explained above and seeds
a vector with the seeds used to execute
each experiment.
Manuel Lopez-Ibañez and Jérémie Dubois-Lacoste
irace.main
a higher-level command-line interface to
irace
.
readScenario
to read the scenario setup from a file.
defaultScenario
to provide a default scenario for irace.
readParameters
to read the target algorithm parameters from a file.
1 2 3 4 5 6 7 | ## Not run:
parameters <- readParameters("parameters.txt")
scenario <- readScenario(filename="scenario.txt",
scenario=defaultScenario())
irace(scenario=scenario, parameters=parameters)
## End(Not run)
|
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