Splits an ML-ready tibble into training and testing (and in some cases validation) sets.
splitMLInputTibble(ml_input_tibble, split = c(0.6, 0.2), seed = 5280)An ML-ready tibble generated by loadMLInputTibble().
This must have a target variable column named either
genome_drug.resistant_phenotype ("Resistant" or "Susceptible "
classification for one bug/drug combination) or resistant_classes
(multi-class classification for determining the drug classes to which each
genome is resistant), but not both.
pillar::num Vector of length 2 indicating the proportion of data to be designated as training and validation, respectively.
pillar::num For reproducible analysis
An rsplit object