makeMBOLearner: Generate default learner.

Description Usage Arguments Value References

View source: R/makeMBOLearner.R

Description

This is a helper function that generates a default surrogate, based on properties of the objective function and the selected infill criterion.

For numeric-only (including integers) parameter spaces without any dependencies:

For mixed numeric-categorical parameter spaces, or spaces with conditional parameters:

If additionally dependencies are in present in the parameter space, inactive conditional parameters are represented by missing NA values in the training design data.frame. We simply handle those with an imputation method, added to the random forest:

Both of these techniques make sense for tree-based methods and are usually hard to beat, see Ding et.al. (2010).

Usage

1
makeMBOLearner(control, fun, config = list(), ...)

Arguments

control

[MBOControl]
Control object for mbo.

fun

[smoof_function]
The same objective function which is also passed to mbo.

config

[named list]
Named list of config option to overwrite global settings set via configureMlr for this specific learner.

...

[any]
Further parameters passed to the constructed learner. Will overwrite mlrMBO's defaults.

Value

[Learner]

References

Ding, Yufeng, and Jeffrey S. Simonoff. An investigation of missing data methods for classification trees applied to binary response data. Journal of Machine Learning Research 11.Jan (2010): 131-170.


mlrMBO documentation built on June 25, 2018, 9:04 a.m.