intersystems-community/fhir-ai-hackathon-kit/iris-integratedml

docker exec -it iris-fhir bash
python3 -m pip install --index-url https://registry.intersystems.com/pypi/simple --no-cache-dir --target /usr/irissys/mgr/python intersystems-iris-automl

-- 1. Split train/test (views do not copy data). Make ranges cover every row exactly once.
CREATE VIEW dc_data.TitanicTrain AS SELECT * FROM dc_data.Titanic WHERE id <= 700
CREATE VIEW dc_data.TitanicTest  AS SELECT * FROM dc_data.Titanic WHERE id > 700
 
-- 2. Define model: target column + training data (features auto-selected)
CREATE MODEL TitanicSurvival PREDICTING (Survived) FROM dc_data.TitanicTrain
-- or restrict features:
CREATE MODEL TitanicSurvivalSAF PREDICTING (Survived) WITH (Sex varchar, Age integer, Fare numeric) FROM dc_data.TitanicTrain
 
-- 3. Train
TRAIN MODEL TitanicSurvival
 
-- 4. Validate on held-out data, then read metrics
VALIDATE MODEL TitanicSurvival FROM dc_data.TitanicTest
SELECT * FROM INFORMATION_SCHEMA.ML_VALIDATION_METRICS
 
-- 5. Predict (+ confidence for classification)
SELECT *, PREDICT(TitanicSurvival) AS Prediction, PROBABILITY(TitanicSurvival) AS Probability FROM dc_data.TitanicTest
SELECT * FROM dc_data.TitanicTest WHERE PREDICT(TitanicSurvival) = 1