Logarithmic spacing in grid search during tuning

[doubleml]

Logarithmic spacing in grid search during tuning

[MalteKurz]

The tuning is based on functionalities from mlr3tuning. Therefore, https://mlr3book.mlr-org.com/optimization.html#optimization is often a good resource for such questions.

One way to achieve the requested logarithmic spacing is by applying transformations (see also https://mlr3book.mlr-org.com/optimization.html#tuning). To be more specific, you can use

par_grids = list(
  "ml_g" = paradox::ps(lambda=paradox::p_dbl(-5, 1, trafo = function(x) 10^x)),
  "ml_m" =  ParamSet$new(list(
    ParamDbl$new("lambda", lower = 0.05, upper = 0.1))))

tune_settings = list(terminator = trm("evals", n_evals = 100),
                     algorithm = tnr("grid_search", resolution = 7),
                     rsmp_tune = rsmp("cv", folds = 5),
                     measure = list("ml_g" = msr("regr.mse"),
                                    "ml_m" = msr("regr.mse")))

doubleml_plr$tune(param_set = par_grids, tune_settings = tune_settings)

doubleml_plr$tuning_res

doubleml_plr$tuning_res$X1$ml_g[[1]]$tuning_result[[1]]$tuning_archive %>% arrange(lambda)

This way you get the requested logarithmic spacing for the lambda parameter values.
Note that in doubleml_plr$tuning_res$X1$ml_g[[1]]$tuning_result[[1]]$tuning_archive and doubleml_plr$tuning_res$X1$ml_g[[1]]$tuning_result[[1]]$tuning_result the lambda entries seem to be pre-transformation (basically the exponents of trafo = function(x) 10^x). In contrast the x_domain / learner_param_vals columns seem to contain the transformed / actual parameter values. Note that we here just pass-through the tuning result and archive from mlr3tuning where the tables are filled this way.

[gleb-roma]

This is great, thank you!