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H2O Driverless AI Integration

H2ODriverless AIPartner extensionMOJO
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Sep 16, 2020 3:42 PM
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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.

External resources

  • KNIME H2O Driverless AI Integration User Guide
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.2.2
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

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    knime
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    KNIME H2O Driverless AI IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 1.0.0

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    knime
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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

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