select * from mldb.H2OPredict( on (select * FROM winestrain sample 5) on (select * from mojo_models where model_id = 'bin_wine_mojo_gbm') DIMENSION using Accumulate('wine_id') ModelOutputFields('label','classProbabilities','contributions','leafnodeassignments','stageprobabilities') EnableOptions('leafnodeassignments','stageprobabilities','contributions') ) as td; *** Query completed. 5 rows found. 7 columns returned. *** Total elapsed time was 1 second.
The following example is a snippet of the total output:
wine_id prediction label classprobabilities contributions leafnodeassignments ------------------- ----------- -------------------- ----------------- ------------------------ 5926 0 0 {"0": 0.9968420757426275,"1": 0.0031579242573724358} {"fixed_acidity": -0.013056158,"volatile_acidity": -0.13548231,"citric_acid": 0.0013693329,"residual_sugar": 0.0076238196,"chlorides": -0.83561426,"free_sulfur_dioxide": 0.050528985,"total_sulfur_dioxide": -1.1812251,"density": -0.41103098,"pH": -0.08305049,"sulphates": -0.16572128,"alcohol": -0.02420906,"quality": -3.8396614E-4} [RLLLL, RLLLL, RLLLL, RLLRR, RLLLL, RLRLR, RLLLL, RLLLR, RLRLL, RLLLR, RLRLL, LRLLL, RLLLR, RLLLR, LRLLL, RLLRL, RLLLR, RLLLL, RLLRL, LRLLL, RLLRL, RLLRL, LRRLR, RLLRL, LRLLL, LRRRR, LRLLL, RLRRL, LRLLR, LRRLR, RLRRL, RLLRL, LRLLL, LRLRL, RLRLL, RLLLR, LRRRL, RLRLL, LRLLL, RLRRR, RLRLR, RLLLR, RLRLR, LLLLR, RLRLL, LLLRR, RRLLR, LLRRR, LLLLR, RLRLR] 4137 0 0 {"0": 0.9967583588168474,"1": 0.0032416411831526076} {"fixed_acidity": -0.05196306,"volatile_acidity": -0.2888404,"citric_acid": -0.0043992857,"residual_sugar": -0.2530282,"chlorides": 0.6672683,"free_sulfur_dioxide": -0.015595852,"total_sulfur_dioxide": -2.6713772,"density": 0.07745419,"pH": -0.12731172,"sulphates": 0.023299774,"alcohol": -0.14568566,"quality": 0.026176445} [RLLLL, RLLLL, RLLLL, RLLRR, RLLLL, RLRLR, RLLLL, RLLRL, RLRLR, RLLLR, RLRLL, RRLLL, RLLLR, RLLLR, RRLLL, RLLRL, RLLLR, RLLLL, RLLRL, RRLLL, RLLRL, RLLRL, RRLLL, RLLRL, RRLLL, RRLRL, RRLLL, RLRRL, RRLLR, RRLLL, RLRRL, RLLRL, RRRLL, RRRLL, RLRLL, RLLLR, LRRRL, RLRLL, RLLLR, RLRRR, RLRLR, RLLLR, RLRLR, RRRLR, RLRLL, RRLRR, RRLLR, RLRLL, RLLLL, RLRLR] ...
See Python Code to Generate H2O Open Source Models for the Python codes needed to generate the models.