Build a SuperConfigLive – same shape as setup_SuperConfig but with
in-memory tabular data instead of file paths.
Usage
setup_SuperConfigLive(
dat_training,
dat_validation = NULL,
dat_test = NULL,
weights = NULL,
positive_class = NULL,
preprocessor_config = NULL,
decomposition_config = NULL,
hyperparameters = NULL,
tuner_config = NULL,
outer_resampling_config = NULL,
execution_config = setup_ExecutionConfig(),
question = NULL,
outdir = NULL,
verbosity = 1L
)Arguments
- dat_training
data.frame or data.table. Training data.
- dat_validation
data.frame, data.table, or
NULL.- dat_test
data.frame, data.table, or
NULL.- weights
Optional Character: Column name in
dat_trainingused as observation weights.- positive_class
Optional Character: For binary classification, the outcome level to treat as positive; forwarded to train which reorders the outcome factor via set_positive_class.
NULLkeeps the existing level order.- preprocessor_config, hyperparameters, tuner_config, outer_resampling_config, execution_config, question, verbosity
See setup_SuperConfig.
- decomposition_config
DecompositionConfigobject: Configuration for data decomposition.- outdir
Optional Character: Output directory;
NULLmeans "do not write to disk" (the rtemislive case).
Examples
scl <- setup_SuperConfigLive(
dat_training = iris,
hyperparameters = setup_LightGBM(),
outer_resampling_config = setup_Resampler(),
question = "Can we tell iris species apart given their measurements?"
)