Input
- InputTable: svm_iris_test (see SVMDense Examples Input)
- Model: densesvm_iris_sigmoid_model (see SVMDense Example: Sigmoid Model)
SQL Call
SELECT * FROM SVMDensePredict (
ON svm_iris_test AS InputTable PARTITION BY ANY
ON densesvm_iris_sigmoid_model AS Model DIMENSION
USING
IdColumn ('id')
TargetColumns ('[1:4]')
Accumulate ('id','species')
Responses ('virginica')
) AS dt ORDER BY 3 DESC;
Output
id prediction prob_virginica species --- ---------- ------------------- ---------- 110 virginica 0.8243513170061639 virginica 130 virginica 0.8196895545919612 virginica 145 virginica 0.819689554376522 virginica 125 virginica 0.8196895541344449 virginica 140 virginica 0.8196895537732645 virginica 105 virginica 0.7827050534303357 virginica 55 virginica 0.7493463554983981 versicolor 75 virginica 0.7024598410529389 versicolor 135 virginica 0.613145720806066 virginica 150 virginica 0.5827460668964375 virginica 115 versicolor 0.38810199423491243 virginica 120 versicolor 0.3082683626614083 virginica 15 versicolor 0.262430284210736 setosa 100 versicolor 0.2624297267110863 versicolor 85 versicolor 0.2576096538956448 versicolor 95 setosa 0.23194834526579422 versicolor 65 setosa 0.21744242477000916 versicolor 80 setosa 0.19113697852593411 versicolor 70 setosa 0.177655546064284 versicolor 90 setosa 0.1737892075977879 versicolor 60 setosa 0.1261779290285922 versicolor 45 setosa 0.12548856100182576 setosa 20 setosa 0.10808401281711943 setosa 50 setosa 0.09658624605309041 setosa 25 setosa 0.09646076478211794 setosa 10 setosa 0.09451432260095656 setosa 35 setosa 0.09451411796130273 setosa 40 setosa 0.09353276878398742 setosa 5 setosa 0.09353245790680728 setosa 30 setosa 0.09007237627853645 setosa
Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.