This workflow shows how to utilize H2O Driverless AI in KNIME to create a model. It starts off with data ingestion and preprocessing, then sends the data to Driverless AI instance to run an experiment. The corresponding MOJO is then created and returned to KNIME where it is applied on the hold-out set. To utilize this workflow, you will need an instance of Driverless AI.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.2.2
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