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Four Techniques for Outlier Detection

Preprocessing Outlier Data cleaning Z-score DBSCAN
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This workflow accesses a sample of data from the airline dataset and detects outlier airports based on the average arrival delay in them. The techniques applied are numeric outlier, z-score, DBSCAN and isolation forest. The outlier airports detected by each of these techniques are visualized on a map of US using the KNIME OSM integration.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.2 Note: Not all extensions may be displayed.
  • KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.1.1, 4.1.2

  • KNIME Interactive R Statistics Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.1.0, 4.1.2

  • KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Open Street Map Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.1.1, 4.1.2

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