Input
- InputTable: shapelets_test, which has additional data from the data set used to train the model
- Model: shapelets_model, output table of ShapeletSupervised Example
| id | period | stockprice | stock_category |
|---|---|---|---|
| 5 | 22418 | 460 | Technology |
| 5 | 22419 | 457 | Technology |
| 5 | 22420 | 452 | Technology |
| 5 | 22421 | 459 | Technology |
| 5 | 22422 | 462 | Technology |
| 5 | 22423 | 459 | Technology |
| 5 | 22424 | 463 | Technology |
| 5 | 22425 | 479 | Technology |
| 5 | 22426 | 493 | Technology |
| 5 | 22427 | 490 | Technology |
| ... | ... | ... | ... |
SQL Call
CREATE MULTISET TABLE shapelets_predict AS (
SELECT * FROM ShapeletSupervisedClassifier (
ON shapelets_test AS InputTable PARTITION BY id ORDER BY period
ON shapelets_model AS Model DIMENSION ORDER BY shapelet_id, time_instant
USING
TimeInterval (1)
TargetColumn ('stockprice')
Accumulate ('stock_category')
) AS dt
) WITH DATA;
Output
SELECT * FROM shapelets_predict ORDER BY 1;
The column stock_category contains the original category.
id predicted_category stock_category -- ------------------ -------------- 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 5 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 6 technology technology 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 7 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare 8 healthcare healthcare
Prediction Accuracy
SELECT (SELECT COUNT(id) FROM shapelets_predict WHERE predicted_category = stock_category)/ (SELECT COUNT(id) FROM shapelets_predict) AS prediction_accuracy;
prediction_accuracy
-------------------
1
The prediction accuracy is 100% because the predicted and original categories are the same.
Download a zip file of all examples and a SQL script file that creates their input tables.