PREDICT_PMML
Applies an imported PMML model on an input relation. The function returns the result that would be expected for the model type encoded in the PMML model.
PREDICT_PMML returns NULL in the following cases:
-
the predictor is an invalid or NULL value
-
the categorical predictor is of an unknown class
Note
PREDICT_PMML returns values of complex type ROW for models that use the Output tag. Vertica does not currently support directly inserting this data into a table.
You can work around this limitation by changing the output to JSON with TO_JSON before inserting it into a table:
=> CREATE TABLE predicted_output AS SELECT TO_JSON(PREDICT_PMML(X1,X2,X3
USING PARAMETERS model_name='pmml_imported_model'))
AS predicted_value
FROM input_table;
Syntax
PREDICT_PMML ( input-columns
USING PARAMETERS model_name = 'model-name' [, match_by_pos = match-by-position] )
Arguments
input-columns- Comma-separated list of columns to use from the input relation, or asterisk (*) to select all columns.
Parameters
| Parameter | Description |
|---|---|
model_name |
Name of the model (case-insensitive). The function supports PMML models that encode the following model types:
|
match_by_pos |
Boolean value that specifies how input columns are matched to model features:
|
Examples
In this example, the function call uses all the columns from the table as predictors and predicts the value using the 'my_kmeans' model in PMML format:
SELECT PREDICT_PMML(* USING PARAMETERS model_name='my_kmeans') AS predicted_label FROM table;
In this example, the function call takes only columns col1, col2 as predictors, and predicts the value for each row using the 'my_kmeans' model from schema 'my_schema':
SELECT PREDICT_PMML(col1, col2 USING PARAMETERS model_name='my_schema.my_kmeans') AS predicted_label FROM table;
In this example, the function call returns an error as neither schema nor model-name can accept * as a value:
SELECT PREDICT_PMML(* USING PARAMETERS model_name='*.*') AS predicted_label FROM table;
SELECT PREDICT_PMML(* USING PARAMETERS model_name='*') AS predicted_label FROM table;
SELECT PREDICT_PMML(* USING PARAMETERS model_name='models.*') AS predicted_label FROM table;