Prepare a dataset for analysis

Transform a dataset with named columns into a list with features (x) and response (y) elements.

dataset_prepare(dataset, x, y = NULL, named = TRUE,
  named_features = FALSE, parallel_records = NULL)

Arguments

dataset	A dataset
x	Features to include. When `named_features` is `FALSE` all features will be stacked into a single tensor so must have an identical data type.
y	(Optional). Response variable.
named	`TRUE` to name the dataset elements "x" and "y", `FALSE` to not name the dataset elements.
named_features	`TRUE` to yield features as a named list; `FALSE` to stack features into a single array. Note that in the case of `FALSE` (the default) all features will be stacked into a single 2D tensor so need to have the same underlying data type.
parallel_records	(Optional) An integer, representing the number of records to decode in parallel. If not specified, records will be processed sequentially.

A dataset. The dataset will have a structure of either:

When named_features is TRUE: list(x = list(feature_name = feature_values, ...), y = response_values)
When named_features is FALSE: list(x = features_array, y = response_values), where features_array is a Rank 2 array of (batch_size, num_features).

Note that the y element will be omitted when y is NULL.