Input
- InputTable: svm_iris_test (see SVMDense Examples Input)
- Model: densesvm_iris_polynomial_model (see SVMDense Example: Polynomial Model)
SQL Call
SELECT * FROM SVMDensePredict (
ON svm_iris_test AS InputTable PARTITION BY ANY
ON densesvm_iris_polynomial_model AS Model DIMENSION
USING
IdColumn ('id')
TargetColumns ('[1:4]')
Accumulate ('id','species')
) AS dt ORDER BY id;
Output
id predict_value predict_confidence species --- ------------- --------------------- ---------- 10 setosa 9.98769473221666E-001 setosa 5 setosa 9.99937759758809E-001 setosa 65 versicolor 9.99999999893766E-001 versicolor 20 setosa 9.99961221612293E-001 setosa 60 versicolor 9.99998361499087E-001 versicolor 75 versicolor 1.00000000000000E 000 versicolor 115 virginica 1.00000000000000E 000 virginica 90 versicolor 9.99999998869915E-001 versicolor 130 versicolor 9.99999999999998E-001 virginica 25 setosa 9.90297655725013E-001 setosa 145 virginica 1.00000000000000E 000 virginica 40 setosa 9.99871345035593E-001 setosa 80 versicolor 9.99999998816400E-001 versicolor 120 versicolor 6.20924228853934E-001 virginica 55 versicolor 9.99999999999998E-001 versicolor 95 versicolor 9.99999999986587E-001 versicolor 135 virginica 9.99997037038602E-001 virginica 110 virginica 1.00000000000000E 000 virginica 150 virginica 9.99055086556359E-001 virginica 35 setosa 9.98705595423770E-001 setosa 50 setosa 9.99748925296680E-001 setosa 105 virginica 1.00000000000000E 000 virginica 15 setosa 9.99999822892320E-001 setosa 30 setosa 9.98748168562453E-001 setosa 70 versicolor 9.99999999999670E-001 versicolor 45 setosa 9.99900491699706E-001 setosa 85 versicolor 9.99999999885339E-001 versicolor 125 virginica 1.00000000000000E 000 virginica 100 versicolor 9.99999999999295E-001 versicolor 140 virginica 1.00000000000000E 000 virginica
Download a zip file of all examples and a SQL script file that creates their input tables.