create_partitions: Create data partitions
In alexWhitworth/glmEnsemble: Builds GLM ensemble models in parallel

Create n data partitions for training with equal sized classes via resampling.

1 2	create_partitions(df, dep_var, level = NULL, n = 100L, major_class_wt = 1, seed = 379L, test_pct = 0.33, binomial = TRUE)

`df`	A `data.frame` for analysis
`dep_var`	A character string denoting the dependent variable in `df`.
`level`	level of interest. If `NULL` takes the 2nd level of a factor variable or the 2nd unique value from a non-factor variable.
`n`	An integer denoting the number of ensembles to build. Defaults to `100L`.
`major_class_wt`	Controls the number of major class cases selected in each partition as a multiple of the number of minority class observations. Defaults to `1`, which will produce equal sized sets of minority and non-minority class in each partition. Must be greater than or equal to 1.
`seed`	An integer. Seed for reproducibility. Defaults to `379L`.
`test_pct`	A number in (0,1) specifying the size of the test dataset as a percentage. Defaults to `0.33`
`binomial`	Logical. Does the response variable follow a Binomial distribution? Defaults to `TRUE`.