imputeAlgoPerf {aslib} | R Documentation |
Imputes algorithm performance for runs which have NA performance values.
Description
The following formula is used for imputation:
base +- range.scalar * range.span + N(0, sd = jitter * range.span)
With range.span = max - min
.
Returns an object like algo.runs
of asscenario
, but drops
the runstatus and all other measures.
Usage
imputeAlgoPerf(
asscenario,
measure,
base = NULL,
range.scalar = 0.3,
jitter = 0,
impute.zero.vals = FALSE
)
Arguments
asscenario |
[ASScenario ]
Algorithm selection scenario.
|
measure |
[character(1) ]
Measure to impute.
Default is first measure in scenario.
|
base |
[numeric(1) ]
See formula.
Default is NULL , which means maximum of performance values if measure should be minimized,
or minimum for maximization case.
|
range.scalar |
[numeric(1) ]
See formula.
Default is 0.3.
|
jitter |
[numeric(1) ]
See formula.
Default is 0.
|
impute.zero.vals |
[logical(1) ]
Should values which are exactly 0 be imputed to 1e-6?
This allows to take the logarithm later on, handy for subsequent visualizations.
Note that this really only makes sense for non-negative measures!
Default is FALSE.
|
Value
[data.frame
].
[Package
aslib version 0.1.2
Index]