Input
Input tables are from DecisionTree Example: Create Model:
- AttributeTable: iris_attribute_test
- Model: iris_attribute_output_prob
SQL Call
CREATE MULTISET TABLE adaboost_predict AS (
SELECT * FROM AdaBoostPredict (
ON iris_attribute_test AS AttributeTable PARTITION BY pid
ON iris_attribute_output_ab AS Model DIMENSION ORDER BY classifier_id, node_id
USING
AttrTableGroupbyColumns ('attribute')
AttrTablePidColumns ('pid')
AttrTableValColumn ('attrvalue')
OutputProb ('true')
Responses('1','2','3')
) AS dt
) WITH DATA;
Output
SELECT * FROM adaboost_predict ORDER BY pid;
pid pred_label prob_for_label_1 prob_for_label_2 prob_for_label_3 --- ---------- ---------------- ---------------- ---------------- 5 1 0.99621 0.00379 0 10 1 0.99621 0.00379 0 15 1 1 0 0 20 1 0.99621 0.00379 0 25 1 0.97673 0.02327 0 30 1 0.99621 0.00379 0 35 1 0.99621 0.00379 0 40 1 0.99621 0.00379 0 45 1 0.97673 0.02327 0 50 1 0.99621 0.00379 0 55 2 0.00714 0.95673 0.03613 60 2 0.01871 0.94384 0.03745 65 2 0.00714 0.95673 0.03613 70 2 0.00702 0.95747 0.03551 75 2 0.00681 0.95876 0.03443 80 2 0.00702 0.95747 0.03551 85 3 0 0.06343 0.93657 90 2 0.01897 0.94711 0.03392 95 2 0.00681 0.95876 0.03443 100 2 0.00681 0.95876 0.03443 105 3 0 0.09791 0.90209 110 3 0 0.13878 0.86122 115 3 0 0.02477 0.97523 120 2 0.01651 0.9039 0.07959 125 3 0 0.10719 0.89281 130 2 0.00694 0.98026 0.0128 135 2 0.01655 0.90962 0.07383 140 3 0 0.09791 0.90209 145 3 0 0.10719 0.89281 150 3 0 0.04876 0.95124
Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.