GriDiSL: Discrete Super Learner with Grid-Search for Longitudinal Data

Convert factors to binary indicators, for factors with > 2 levels drop the first factor level and define several dummy variables for the rest of the levels

1	factor_to_dummy(data, skip_vars, drop_factor = FALSE, verbose = FALSE)

`data`	Input dataset, as `data.table`.
`skip_vars`	These columns will not be converted
`drop_factor`	Drop the factor variables that were re-coded into binary dummies from the resulting analytic dataset?
`verbose`	Print processing info