lhdTuner: Perform LHD tuning.
In TDMR: Tuned Data Mining in R
Description
Usage
Arguments
Value
View source: R/tdmDispatchTuner.r
Description
Perform a parameter tuning using a Latin hypercube design (LHD)
for obtaining best design points. LHD is performed by configuring SPOT
in such a way that all the budget is used for the initial design (usually LHD).
Usage
1
lhdTuner(confFile, theSpotPath, tdm, envT, dataObj)
Arguments
confFile
task configuration for tuning algorithm
theSpotPath
needed for spot
tdm
the TDMR object
envT
the environment variable
dataObj
the TDMdata object containing the data set (train/vali part and test part)
Value
the result of LHD sampling, i.e. the list spotConfig
TDMR documentation built on March 3, 2020, 1:06 a.m.
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Description Usage Arguments Value
View source: R/tdmDispatchTuner.r
Description
Perform a parameter tuning using a Latin hypercube design (LHD) for obtaining best design points. LHD is performed by configuring SPOT in such a way that all the budget is used for the initial design (usually LHD).
Usage
1 | lhdTuner(confFile, theSpotPath, tdm, envT, dataObj)
|
Arguments
confFile |
task configuration for tuning algorithm |
theSpotPath |
needed for spot |
tdm |
the TDMR object |
envT |
the environment variable |
dataObj |
the |
Value
the result of LHD sampling, i.e. the list spotConfig
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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