1.1 - 8.10 - HMMSupervised Syntax Elements - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)
InitStateTable
[Optional] Specify the name for the initial state probability table that the function outputs.
Default: Pi in the current schema
StateTransitionTable
[Optional] Specify the name for the state transition probability table that the function outputs.
Default: A in the current schema
EmissionTable
[Optional] Specify the name for the emission probability table that the function outputs.
Default: B in the current schema
ModelColumn
[Required if PARTITION BY clause specifies model_key, disallowed otherwise.] Specify the name of the input column that contains the model attributes. The model_column must match a model_key in the PARTITION BY clause. The values in the columns can be either integers or strings.
SeqColumn
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.
ObservationColumn
Specify the name of the Vertices column that contains the observed symbols. The function scans the Vertices table to find all possible observed symbols.
Observed symbols are case-sensitive.
StateColumn
Specify the names of the Vertices columns that contain the state attributes. The state attributes are case-sensitive.
SkipColumn
[Optional] Specify the name of the Vertices column whose value determines whether the function skips the row. Each value in this column must be an INTEGER or VARCHAR that represents the value true or false (INTEGER 1 or 0 or VARCHAR 'true', 't', 'yes', 'y', '1', 'false', 'f', 'no', 'n', or '0'). If the value represents true, the function skips the row; otherwise it does not.
Default behavior: The function does not skip any rows.
BatchSize
[Optional] Specify the number of models to process. The batch_size must be a positive INTEGER value. If you specify batch_size and there is insufficient free memory, the function reduces the batch size.
Default behavior: The function determines the batch size dynamically, based on memory conditions.