select * from mldb.H2OPredict(
on (select top 10 * from iris_input)
on (select model_id, model, h2o_lic.license from h2o_models where model_id = 'h2odai_iris_model') DIMENSION
using
Accumulate('id')
ModelType('DAI')
MODELOUTPUTFIELDS('species.0', 'species.1', 'species.2')
) as td;
*** Query completed. 10 rows found. 5 columns returned.
*** Total elapsed time was 1 second.
id prediction species.0 species.1 species.2
-- ----------- ---------------- ------------------ -----------------
120 0.022511249718785317 0.8587316860102785 0.11875706427093613
118 0.010271546391597528 0.02267639045773728 0.9670520631506652
55 0.022511249718785317 0.8587316860102785 0.11875706427093613
95 0.01795072789830224 0.9597371137030228 0.02231215839867505
72 0.01795072789830224 0.9597371137030228 0.02231215839867505
112 0.010271546391597528 0.02267639045773728 0.9670520631506652
135 0.021124703155354245 0.9212999851682955 0.05757531167635035
57 0.02577399911196362 0.616935847658933 0.35729015322910346
80 0.023298099547984594 0.9497460586086773 0.02695584184333808
40 0.9697824957862801 0.019504773948357475 0.010712730265362513
+---------+---------+---------+---------+---------+---------+--------+