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Re-Engineering the variable importance by feeding the Score (of a binary classification) into a numeric model that provides variable importance

H2oModelImportanceVariable importance
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Aug 31, 2022 6:49 PM
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Re-Engineering the variable importance by feeding the Score (of a binary classification) into a numeric model that provides variable importance

External resources

  • forum entry
  • UCI - Census Income Data Set
  • node - Global Feature Importance
  • Understand Your ML Model with Global Feature Importance
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Created with KNIME Analytics Platform version 4.6.1
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    KNIME Base nodesTrusted extension

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    Version 4.6.1

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    KNIME Data GenerationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Extension for Big Data File FormatsTrusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME H2O Machine Learning IntegrationTrusted extension

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    KNIME H2O Machine Learning Integration - MOJO ExtensionTrusted extension

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    Version 4.6.0

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    KNIME Statistics NodesTrusted extension

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    KNIME XGBoost IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

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