Input
- AttributeTable: iris_attribute_test, is from DecisionTree Example: Create Model
- ModelTable: iris_attribute_output_prob, is from DecisionTree Example: OutputProb
SQL Call
CREATE MULTISET TABLE singletree_predict2 AS ( SELECT * FROM DecisionTreePredict_MLE ( ON iris_attribute_test AS AttributeTable PARTITION BY pid ON iris_attribute_output_prob AS Model DIMENSION USING AttrTableGroupbyColumns ('attribute') AttrTablePidColumns ('pid') AttrTableValColumn ('attrvalue') OutputProb ('true') Responses('1','2','3') ) AS dt ) WITH DATA;
Output
SELECT * FROM singletree_predict2 ORDER BY pid;
pid pred_label prob_for_label_1 prob_for_label_2 prob_for_label_3 --- ---------- ---------------- ---------------- ---------------- 5 1 0.95348 0.02326 0.02326 10 1 0.95348 0.02326 0.02326 15 1 0.95348 0.02326 0.02326 20 1 0.95348 0.02326 0.02326 25 1 0.95348 0.02326 0.02326 30 1 0.95348 0.02326 0.02326 35 1 0.95348 0.02326 0.02326 40 1 0.95348 0.02326 0.02326 45 1 0.95348 0.02326 0.02326 50 1 0.95348 0.02326 0.02326 55 2 0.02632 0.94736 0.02632 60 2 0.02632 0.94736 0.02632 65 2 0.02632 0.94736 0.02632 70 2 0.02632 0.94736 0.02632 75 2 0.02632 0.94736 0.02632 80 2 0.02632 0.94736 0.02632 85 2 0.02632 0.94736 0.02632 90 2 0.02632 0.94736 0.02632 95 2 0.02632 0.94736 0.02632 100 2 0.02632 0.94736 0.02632 105 3 0.0625 0.125 0.8125 110 3 0.07692 0.07692 0.84616 115 3 0.0625 0.0625 0.875 120 2 0.14286 0.57143 0.28571 125 3 0.07692 0.07692 0.84616 130 2 0.14286 0.57143 0.28571 135 2 0.14286 0.57143 0.28571 140 3 0.0625 0.125 0.8125 145 3 0.07692 0.07692 0.84616 150 3 0.25 0.25 0.5
Download a zip file of all examples and a SQL script file that creates their input tables.