PREDICT_SVM_CLASSIFIER
Applies an SVM model on an input table or view.
Important: Before using a machine learning function, be aware that all the ongoing transactions might be committed.
Syntax
PREDICT_SVM_CLASSIFIER (input_columns USING PARAMETERS model_name='model_name' [, match_by_pos = 'method'])
Arguments
input_columns |
A comma-separated list of the columns to be used for prediction. |
Parameters
model_name='model_name' |
The name of the model. Model names are case-insensitive. |
match_by_pos= 'method' |
(Optional) Valid Values:
|
Return
Return data type: FLOAT |
Returns the predicted value. |
Examples
This example shows how you can use the PREDICT_SVM_CLASSIFIER function on the mtcars table:
=> SELECT PREDICT_SVM_CLASSIFIER (mpg,cyl,disp,wt,qsec,vs,gear,carb USING PARAMETERS model_name='mySvmClassModel') FROM mtcars;
PREDICT_SVM_CLASSIFIER
------------------------ 0 0 1 0 0 1 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 1 1 1 1 0 0 0
(32 rows)
This example shows how you can use the PREDICT_SVM_CLASSIFIER function on the mtcars table, using the match_by_pos
parameter. Note that you can any of the column inputs with a constant that does not match an input column. In this example, the mpg column was replaced with the constant 40:
=> SELECT PREDICT_SVM_CLASSIFIER (40,cyl,disp,wt,qsec,vs,gear,carb USING PARAMETERS model_name='mySvmClassModel', match_by_pos ='true') FROM mtcars;
PREDICT_SVM_CLASSIFIER
------------------------ 0 0 0 0 1 0 0 1 1 1 1 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 1 1 0 0 1
(32 rows)