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13_Binary_Classification_Inspector

Binary classificationMachine learning modelBayesianRandomForestXGBoost Tree
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Versionv1.1Latest, created on 
Feb 16, 2025 10:31 PM
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Binary Classification Inspector Example

This workflow demonstrates the functionality of the Binary Classification Inspector node. It produces a complex view made of four different charts in order to compare, optimize and select predictions of different binary classifiers.

It is possible to compare a number of binary classifier machine learning models predicting the same target on the same test data using performance metrics and ROC curves. Here three machine learning models are used: Bayesian, RandomForest, and XGBoost Tree.

By moving a threshold slider in the interactive view you can optimize a model by finding the best threshold given a performance metric of your choice.

It is possible to interactively select a given type of predictions (e.g. true positives) of one of the models and export them at the output of the node
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Used extensions & nodes

Created with KNIME Analytics Platform version 5.4.0
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    KNIME Base Chemistry Types & NodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    KNIME Ensemble Learning WrappersTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    KNIME Machine Learning Interpretability ExtensionTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    KNIME XGBoost IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.4.0

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    RDKit Nodes FeatureTrusted extension

    Novartis

    Version 5.2.0

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