CALL td_analyze (
'factorscore',
'required_parameter_list [ optional_parameter; [...] ]'
);
- required_parameter_list
database = input_database_name;
tablename = input_table_name;
modeldatabase = model_database_name;
modeltablename = model_table_name;
- optional_parameter
{ gensqlonly = { true | false } |
index = column_name [,...] |
outputdatabase = output_database_name |
outputtablename = output_table_name |
overwrite = { true | false } |
retain = column_name [,...] |
samplescoresize = sample_score_size |
scoringmethod = { score | evaluate | scoreandevaluate }
}
Syntax Elements
- database
- The database containing the input table.
- tablename
- The name of the input table to score.
- modeldatabase
- The database containing the factor model table.
- modeltablename
- The name of the table containing the factor model to use in scoring, built by the Factor Analysis function.
- gensqlonly
- [Optional] True returns the SQL for the function as a result set but does not run it.
- False runs the SQL for the function but does not return it as a result set.
- Default: false
- index
- [Optional] The columns for the primary index of the score output table. These columns must form a unique key for the score output table. Otherwise, a given observation has more than one score.
- These index columns are included both in the Primary Index clause and the select list.
- Default: Primary index columns of the input table
- outputdatabase
- The database where the output score table will be built. (If the scoring method is not evaluate, this parameter is required.)
- outputtablename
- The name of the output score table to be built. (If the scoring method is not evaluate, this parameter is required.)
- overwrite
- [Optional] Whether to drop the output tables before creating new ones.
- Default: true
- retain
- [Optional] One or more input table columns to copy to the output table.
- samplescoresize
- [Optional] If scoringmethod=score or scoringmethod=scoreandevaluate, the number of output table rows to show in a sample of the result set (an integer).
- Default behavior: Function returns no sample.
- scoringmethod
- [Optional] Whether to score (only), evaluate (only), or score and evaluate.
- With the options evaluate and scoreandevaluate, the function outputs a confusion matrix table in XML format. The table includes counts of predicted and actual values of the dependent variable of the decision tree model and counts of correct and incorrect predictions.
- Default: score