| Argument | Category | Description |
|---|---|---|
| ModelColumn | Optional | The name of the column that contains the model attribute. If you specify this argument, then its value must match a model_key in the PARTITION BY clause. |
| SeqColumn | Required | The name of the column that contains the sequence attribute. The sequence_attribute must be a sequence attribute in the PARTITION BY clause. A sequence must contain more than two observation symbols. |
| ObsColumn | Required | The name of the column that contains the observed symbols. The function scans the input table to find all possible observed symbols. Observed symbols are case-sensitive.
|
| StateColumn | Required | The state attributes. You can specify multiple states. The states are case-sensitive. |
| SkipColumn | Optional | The name of the column whose values determine whether the function skips the row. The function skips the row if the value is “true”, “yes”, “y”, or “1”. The function does not skip the row if the value is “false”, “f”, “no”, “n”, “0”, or NULL. |
| OutputTables | Optional | The names of the output tables: init_state_prob—Initial state probability table (default name is Pi). state_transition_prob—State transition probability table (default name is A). emit_prob—Emission probability table (default name is B). |
| BatchSize | Optional | The number of models to process. The size must be positive. If the batch size is not specified, the function avoids out-of-memory errors by determining the appropriate size. If the batch size is specified and there is insufficient free memory, the function reduces the batch size. The batch size is determined dynamically, based on the memory conditions. For example, at time T1, the specified batch size 1000 might be adjusted to 980, and at time T2, the batch size might be adjusted to 800. |