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  • 01_Deploying_and_Validating_models_as_WebServices
WorkflowWorkflow

Validating KNIME Workflows

Reproducibility Validation Testing XGBoost RDKit
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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

Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.0
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    KNIME profile image
    knime
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    KNIME Ensemble Learning Wrappers Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    KNIME profile image
    knime
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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    KNIME profile image
    knime
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    KNIME JSON-Processing Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    KNIME profile image
    knime
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    KNIME Testing Framework Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.3.0, 4.5.0

    KNIME profile image
    knime
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    KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    KNIME profile image
    knime
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    RDKit Nodes Feature Trusted extension

    NIBR

    Version 4.5.0

    manuelschwarze
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