Use the ModelOutputFields argument to create an output column based on a specific output from the model instead of getting all of the output fields in one generic column json report.
select * from mldb.ONNXPredict( on (select * sample 10 from iris_test ) on (select * from onnx_models where model_id='sklearn_rf_iris_model') DIMENSION using Accumulate('sepal_length') modelOutputFields('output_probability') OverWriteCachedModel('sklearn_rf_iris_model') // same effect as using ‘*’ or ‘true’ – In this example, a new version of the model is replacing the current version in the cache. ) as td ; *** Query completed. 10 rows found. 2 columns returned. *** Total elapsed time was 1 second.
sepal_length output_probability -------------------- ------------------------------------------------------- 5.60000000000000E 000 {"0":0.0,"1":0.99999934,"2":0.0} 6.70000000000000E 000 {"0":0.0,"1":0.0,"2":0.99999934} 5.00000000000000E 000 {"0":0.99999934,"1":0.0,"2":0.0} 5.10000000000000E 000 {"0":0.99999934,"1":0.0,"2":0.0} 6.90000000000000E 000 {"0":0.0,"1":0.0,"2":0.99999934} 5.10000000000000E 000 {"0":0.99999934,"1":0.0,"2":0.0} 6.50000000000000E 000 {"0":0.0,"1":0.98999935,"2":0.01} 6.70000000000000E 000 {"0":0.0,"1":0.0,"2":0.99999934} 6.10000000000000E 000 {"0":0.0,"1":0.12999998,"2":0.86999947} 4.90000000000000E 000 {"0":0.99999934,"1":0.0,"2":0.0}