syne_tune.experiments.benchmark_definitions.lcbench module

syne_tune.experiments.benchmark_definitions.lcbench.lcbench_benchmark(dataset_name, datasets=None)

The default is to use nearest neighbour regression with K=1. If you use a more sophisticated surrogate, it is recommended to also define add_surrogate_kwargs, for example:

surrogate="RandomForestRegressor",
add_surrogate_kwargs={
    "predict_curves": True,
    "fit_differences": ["time"],
},

Parameters:

• dataset_name (str) – Value for dataset_name

• datasets – Used for transfer learning

Return type:

SurrogateBenchmarkDefinition

Returns:

Definition of benchmark