mlr_optimizers_async_grid_search {bbotk} | R Documentation |
Asynchronous Optimization via Grid Search
Description
OptimizerAsyncGridSearch
class that implements a grid search.
The grid is constructed as a Cartesian product over discretized values per parameter, see paradox::generate_design_grid()
.
The points of the grid are evaluated in a random order.
Dictionary
This Optimizer can be instantiated via the dictionary
mlr_optimizers or with the associated sugar function opt()
:
mlr_optimizers$get("async_grid_search") opt("async_grid_search")
Parameters
batch_size
integer(1)
Maximum number of points to try in a batch.
Super classes
bbotk::Optimizer
-> bbotk::OptimizerAsync
-> OptimizerAsyncGridSearch
Methods
Public methods
Inherited methods
Method new()
Creates a new instance of this R6 class.
Usage
OptimizerAsyncGridSearch$new()
Method optimize()
Starts the asynchronous optimization.
Usage
OptimizerAsyncGridSearch$optimize(inst)
Arguments
inst
Returns
Method clone()
The objects of this class are cloneable with this method.
Usage
OptimizerAsyncGridSearch$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Source
Bergstra J, Bengio Y (2012). “Random Search for Hyper-Parameter Optimization.” Journal of Machine Learning Research, 13(10), 281–305. https://jmlr.csail.mit.edu/papers/v13/bergstra12a.html.