Description Usage Arguments Value Predefined standard infill criteria

The infill criterion guides the model based search process. The most prominent infill criteria, e.g., expected improvement, lower confidence bound and others, are already implemented in mlrMBO. Moreover, the package allows for the creation of custom infill criteria.

1 2 3 4 5 6 7 8 9 | ```
makeMBOInfillCrit(
fun,
name,
id,
opt.direction = "minimize",
components = character(0L),
params = list(),
requires.se = FALSE
)
``` |

`fun` |
[ - points [
`data.frame` ] n points where to evaluate. - models [
`WrappedModel` |`list` ] Model(s) fitted on design. - control [
`MBOControl` ] Control object. - par.set [
`ParamSet` ] Parameter set. - design [
`data.frame` ] Design of already visited points. - iter [
`integer(1)` ] Current iteration. - progress [
`numeric{1}` ] A value between 0 and 1 indicating the progress of the optimization. - attributes [
`logical{1}` ] Are there attributes appended to the return value that should be added to the `OptPath` ?
Important: Internally, this function will be minimized. So the proposals will be where this function is low. |

`name` |
[ |

`id` |
[ |

`opt.direction` |
[ |

`components` |
[ |

`params` |
[ |

`requires.se` |
[ |

[`MBOInfillCrit`

]

- crit.ei
Expected Improvement

- crit.mr
Mean response

- crit.se
Standard error

- crit.cb
Confidence bound with lambda automatically chosen, see

`infillcrits`

- crit.cb1
Confidence bound with lambda=1

- crit.cb2
Confidence bound with lambda=2

- crit.aei
Augmented expected improvement

- crit.eqi
Expected quantile improvement

- crit.dib1
Direct indicator-based with lambda=1

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