builder: Builder
In ntyndall/detectR:

This function provides a useful flow for building custom models based on the neuralnet package with custom data sets and input.

1 2	builder(..., posClass = "N", saveData = FALSE, normalData = 10000, percent = 80, logs = TRUE, nnThresh = 0.01)

`posClass`	A character string, defining the positive class of a dataset, default to `N`.
`saveData`	A boolean value that also saves the model and scaler, as well as returning the results.
`normalData`	An integer value that defines the number of rows of data to sample from the positive class.
`percent`	A double value between 0 and 100 that defines the percentage of data that the normal data should make up the full data set, the remaining percent is split equally among the other negative classes.
`logs`	A boolean value which defines whether logs should be printed to screen, default to `TRUE`.