batch_random_search: Perform batch random search using a paramset.
In artichaud1/cook: A package for Tidy Hyperparameter Tuning

Description Usage Arguments Details Value

If your parameter search is likely to take a long time, this function allows you to do it in batches, saving the result of the search results to disk after each batch. This incurs a penalty in running time, because the assessment splits are recomputed (or 'baked' in 'recipes'). terminology at the beginning of each batch. The smaller the batch size, the bigger the penalty.

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batch_random_search(resamples, recipe, param_set, n, scoring_func, ...,
  batch_size, out_folder = ".", file_prefix = "batch_", overwrite = FALSE,
  verbosity = TRUE)

`resamples`	A data.frame with columns 'splits' and 'id', created using the 'rsample' package.
`recipe`	The recipe to use. See package 'recipes'.
`param_set`	Param set created by calling ParamHelpers::makeParamset.
`n`	Number of parameter combinations to generate.
`scoring_func`	Your custom train/predict/score function. Must take as parameters: a training dataframe the name of the target variable in the training dataframe a list of parameters (these are the hyperparameters we are tuning) an evaluation dataframe dots. These are additional non-tunable parameters that could be passed to the function.
`...`	Optional params passed to train_predict_func.
`batch_size`	Size of the batches.
`out_folder`	Where to save the intermediate batch results. Folder will be created if not found.
`file_prefix`	Used to name the results files.
`overwrite`	Overwrite existing results files or create new ones.
`verbosity`	Integer: level of verbosity, or TRUE/FALSE for max/min verbosity.

'scoring_func' can return a single score as a numeric vector, or multiple scores in a data.frame. The output folder will be scanned for files corresponding to pattern <file_prefix>_n.RDS. If overwrite is false, the outputs of the current run will be witten to files starting at n + 1. Otherwise it starts at 1 (i.e. <file_prefix_1.RDS). Option verbose will print the batch number at the beginning of each batch.

A tidy data.frame, the aggregate result. This is the same as without the batches.

artichaud1/cook documentation built on May 21, 2019, 9:23 a.m.