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Validating KNIME Workflows

ReproducibilityValidationTestingXGBoostRDKit
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Dec 3, 2018 4:24 PM
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This workflow demonstrates a technique to deploy a model prediction workflow as a web service and to validate that it is doing what it's supposed to do. The key is the use of a reference set of input data and the Table Difference Checker in the "Run Tests if Necessary" component at the end of the workflow. The model can be validated in KNIME Analytics Platform using the KNIME Testing Framework and, once it has been deployed as a web service using KNIME Server, can be validated by calling the service without any rows. The workflow itself generates bioactivity predictions for the input molecules using a set of pre-calculated and saved XGBoost models. It is configured so that it can be easily deployed as a REST web service using KNIME server or used as a predictor directly in KNIME Analytics Platform Extensions required; KNIME Testing Framework RDKit XGBoost
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.0
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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    knime
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    KNIME Ensemble Learning WrappersTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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    knime
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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime profile image
    knime
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    KNIME JSON-ProcessingTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime profile image
    knime
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    KNIME Testing FrameworkTrusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.3.0, 4.5.0

    knime profile image
    knime
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    KNIME XGBoost IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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    knime
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    RDKit Nodes FeatureTrusted extension

    NIBR

    Version 4.5.0

    manuelschwarze

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