mlrMBO is a framework for the (sequential) Model Based parameter Optimization. The goal is to optimize numeric or discrete influence parameters of a non-linear black box function like an industrial simulator or a time-consuming algorithm.
In the following we provide an in-depth introduction to mlrMBO. An introductory example serves as a quickstart guide. Note that our focus is on your comprehension of the basic functions and applications. For detailed technical information and manual pages, please refer to the package's manual pages. They are regularly updated and reflect the documentation of the current packages on CRAN.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.