get_dsc_rank {IOHanalyzer} | R Documentation |
Get the matrix of rankings using the DSCtool api for a DataSetList
Description
Get the matrix of rankings using the DSCtool api for a DataSetList
Usage
get_dsc_rank(
dsList,
targets = NULL,
which = "by_RT",
test_type = "AD",
alpha = 0.05,
epsilon = 0,
monte_carlo_iterations = 0,
na.correction = NULL
)
Arguments
dsList |
The DataSetList object |
targets |
Optional list of target values (Runtime or target value) |
which |
Whether to use a fixed-target 'by_RT' perspective or fixed-budget 'by_FV' |
test_type |
Either 'AD' for Anderson-Darling or KS for Kolmogorov-Smirnov tests |
alpha |
Threshold value for statistical significance |
epsilon |
Minimum threshold to have practical difference between algorithms (eDSC) |
monte_carlo_iterations |
How many monte-carlo-simulations to perform (set to 0 to use regular DSC) |
na.correction |
How to deal with missing values. Only used in fixed-target perspective. Options are: - 'NULL': No correction is done. This will likely result in an error, as the DSCtool does not allow for na values - 'PAR-1' Replace missing values with Budget (budget taken from relevant DataSet) - 'PAR-10' Replace missing values with 10*Budget (budget taken from relevant DataSet) - 'ERT' Replace NA values with the Expected Running Time. If all values are NA, this reverts to nr_runs * budget - 'Remove-na' Removes all NA values |
Value
A named list containing a ranked-matrix which has the rankin of each algorithm on each problem, as well as a list of which omnibus tests can be used to further process this data. This can be further analyzed using 'get_dsc_omnibus'
Examples
get_dsc_rank(dsl, na.correction = 'PAR-10')