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#' @field feature_types (`character()`)\cr | ||
#' Stores the feature types the surrogate can handle, e.g. `"logical"`, `"numeric"`, or `"factor"`. | ||
#' A complete list of candidate feature types, grouped by task type, is stored in [`mlr_reflections$task_feature_types`][mlr_reflections]. | ||
#' A complete list of candidate feature types, grouped by task type, is stored in [`mlr_reflections$task_feature_types`][mlr3::mlr_reflections]. |
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#' @field properties (`character()`)\cr | ||
#' Set of properties of the optimizer. | ||
#' Must be a subset of [`bbotk_reflections$optimizer_properties`][bbotk_reflections]. | ||
#' Must be a subset of [`bbotk_reflections$optimizer_properties`][bbotk::bbotk_reflections]. | ||
#' MBO in principle is very flexible and by default we assume that the optimizer has all properties. | ||
#' When fully initialized, properties are determined based on the `loop_function` and `surrogate`. |
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#' @field properties (`character()`)\cr | ||
#' Stores a set of properties/capabilities the surrogate has. | ||
#' A complete list of candidate properties, grouped by task type, is stored in [`mlr_reflections$learner_properties`][mlr_reflections]. | ||
#' A complete list of candidate properties, grouped by task type, is stored in [`mlr_reflections$learner_properties`][mlr3::mlr_reflections]. |
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