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 +---------+---------+---------+---------+---------+---------+--------+