SparseSVMPredictor Example - Teradata Vantage

Input

• Input table: svm_iris_input_test
• Model table: svm_iris_model, the SVMSparse Example output table

SQL Call

CREATE MULTISET TABLE svm_iris_predict_out AS (
  SELECT * FROM SparseSVMPredictor@coprocessor (
    ON svm_iris_input_test AS input PARTITION BY id
    ON svm_iris_model AS model DIMENSION
    USING
    SampleIDColumn ('id')
    AttributeColumn ('attribute')
    ValueColumn ('value1')
    AccumulateLabel ('species')
  ) AS dt
) WITH DATA;

Output

This query returns the following table:

SELECT * FROM svm_iris_predict_out;

Prediction Accuracy

This query returns the prediction accuracy:

SELECT (SELECT count(id)
FROM svm_iris_predict_out
WHERE predict_value = species)/(
  SELECT count(id) FROM svm_iris_predict_out) AS prediction_accuracy;