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Feature Importance based on RF

Feature Importance Variable Importance Feature Selection Python KNIME integration Conda Python and KNIME

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This Workflow demonstrates the usage of the Component "RF Feature Importance". It can be used in binary classification scenario to calculate the feature/variable importance. Pre-Requisites - KAP 4.3 and higher - Conda installed on local system (https://docs.knime.com/2019-06/python_installation_guide/index.html)

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.1 Note: Not all extensions may be displayed.
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • KNIME Database Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

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