- x
(Optional) A vector containing the names or indices of the predictor variables to use in building the model.
If x is missing, then all columns except event_column, start_column and stop_column are used.

- event_column
The name of binary data column in the training frame indicating the occurrence of an event.

- training_frame
Id of the training data frame.

- model_id
Destination id for this model; auto-generated if not specified.

- start_column
Start Time Column.

- stop_column
Stop Time Column.

- weights_column
Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from
the dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative
weights are not allowed. Note: Weights are per-row observation weights and do not increase the size of the
data frame. This is typically the number of times a row is repeated, but non-integer values are supported as
well. During training, rows with higher weights matter more, due to the larger loss function pre-factor. If
you set weight = 0 for a row, the returned prediction frame at that row is zero and this is incorrect. To get
an accurate prediction, remove all rows with weight == 0.

- offset_column
Offset column. This will be added to the combination of columns before applying the link function.

- stratify_by
List of columns to use for stratification.

- ties
Method for Handling Ties. Must be one of: "efron", "breslow". Defaults to efron.

- init
Coefficient starting value. Defaults to 0.

- lre_min
Minimum log-relative error. Defaults to 9.

- max_iterations
Maximum number of iterations. Defaults to 20.

- interactions
A list of predictor column indices to interact. All pairwise combinations will be computed for the list.

- interaction_pairs
A list of pairwise (first order) column interactions.

- interactions_only
A list of columns that should only be used to create interactions but should not itself participate in model
training.

- use_all_factor_levels
`Logical`

. (Internal. For development only!) Indicates whether to use all factor levels. Defaults to
FALSE.

- export_checkpoints_dir
Automatically export generated models to this directory.

- single_node_mode
`Logical`

. Run on a single node to reduce the effect of network overhead (for smaller datasets) Defaults
to FALSE.