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mlrintermbo  

Model-Based Optimization for 'mlr3' Through 'mlrMBO'
View on CRAN: Click here


Download and install mlrintermbo package within the R console
Install from CRAN:
install.packages("mlrintermbo")

Install from Github:
library("remotes")
install_github("cran/mlrintermbo")

Install by package version:
library("remotes")
install_version("mlrintermbo", "0.5.0")



Attach the package and use:
library("mlrintermbo")
Maintained by
Martin Binder
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-01
Latest Update: 2021-03-01
Description:
The 'mlrMBO' package can ordinarily not be used for optimization within 'mlr3', because of incompatibilities of their respective class systems. 'mlrintermbo' offers a compatibility interface that provides 'mlrMBO' as an 'mlr3tuning' 'Tuner' object, for tuning of machine learning algorithms within 'mlr3', as well as a 'bbotk' 'Optimizer' object for optimization of general objective functions using the 'bbotk' black box optimization framework. The control parameters of 'mlrMBO' are faithfully reproduced as a 'paradox' 'ParamSet'.
How to cite:
Martin Binder (2021). mlrintermbo: Model-Based Optimization for 'mlr3' Through 'mlrMBO'. R package version 0.5.0, https://cran.r-project.org/web/packages/mlrintermbo
Previous versions and publish date:
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Other R packages that mlrintermbo depends, imports, suggests or enhances
Functions, R codes and Examples using the mlrintermbo R package
Some associated functions: OptimizerInterMBO . captureSpecials . makeMlr3Surrogate . mlrintermbo-package . 
Some associated R codes: CapsuledMlr3Learner.R . ParamHelpersParamSet.R . TunerInterMBO.R . optimize.R . paramset.R . surrogates.R . utils.R . zzz.R .  Full mlrintermbo package functions and examples
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