Creates summary data.frame for algorithm performance values across all instances.
convertAlgoPerfToWideFormat
Converts algo.runs object of a scenario to wide format.
Creates a registry which can be used for running several Llama models on a cluster.
Convert an ASScenario scenario object to a llama data object.
Writes an algorithm selection scenario to a directory.
Creates a table that shows the dominance of one algorithm over another one.
Returns feature step names of scenario.
Bakes presolving stuff into a LLAMA data frame.
Returns feature names of scenario.
Returns instance names of scenario.
EDA plots for performance values of algorithms across all instances.
Returns number of CV folds.
S3 class for ASScenarioDesc.
Checks the feature data set for duplicated instances.
getCostsAndPresolvedStatus
Return wether an instance was presolved and which step did it.
Returns feature costs of scenario, summed over all instances.
Returns algorithm names of scenario.
Convert an ASScenario scenario object to a llama data object with cross-validation folds.
Creates summary data.frame for feature values across all instances.
Create cross-validation splits for a scenario.
Imputes algorithm performance for runs which have NA performance values.
Creates summary data.frame for algorithm runstatus across all instances.
Returns number of CV repetitions.
Return features that are useable for a given set of feature steps.
Creates a data.frame that summarizes the feature steps.
Plots the correlation matrix of the algorithms.
getDefaultFeatureStepNames
Returns the default feature step names of scenario.
Retrieves a scenario from the Coseal Github repository and parses into an S3 object.
Parses the data files of an algorithm selection scenario into an S3 object.