Result of tuning.

Container for results of hyperparameter tuning. Contains the obtained point in search space, its performance values and the optimization path which lead there.

Object members:

learner (Learner)

Learner that was optimized.

control (TuneControl)

Control object from tuning.

x (list)

Named list of hyperparameter values identified as optimal. Note that when you have trafos on some of your params, x will always be on the TRANSFORMED scale so you directly use it.

y (numeric)

Performance values for optimal x.

threshold (numeric)

Vector of finally found and used thresholds if tune.threshold was enabled in TuneControl, otherwise not present and hence NULL.

opt.path (ParamHelpers::OptPath)

Optimization path which lead to x. Note that when you have trafos on some of your params, the opt.path always contains the UNTRANSFORMED values on the original scale. You can simply call trafoOptPath(opt.path) to transform them, or, as.data.frame{trafoOptPath(opt.path)}. If mlr option on.error.dump is TRUE, OptPath will have a .dump object in its extra column which contains error dump traces from failed optimization evaluations. It can be accessed by getOptPathEl(opt.path)$extra$.dump.