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Conditional Density Plot Component Example on the Titanic Dataset

Conditional Density Plot Verified component example

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This simple workflow provides an example on how to use the verified component “Conditional Density Plot”. A general question it helps to answer when trying to find a good predictor for Y from feature X: "Is X a good feature?" A part of this question can be answered by answering instead: "Does the distribution of X change by partitioning with class Y?". Because if it does, X might be good predictor for Y. If it does too well (i.e. 100%), data leakage might be present. Examples analysis is done on the titanic dataset. Each row of the data stands for a passenger, with columns like name, sex, age, booked class, fare, ... and whether he or she survived the incident. The task is to identify a feature that can act as a good predictor whether someone survived. Drag and drop the component in another workflow from its KNIME Hub page (link below) to visualize a different dataset. Apply your custom settings by opening the component dialogue. More information is available in the component description. Note that a Conditional Box Plot can be used for similar, less detailed analysis. The Conditional Density Plot offers more insight on the distribution itself.

External resources

  • Conditional Density Plot component - KNIME Hub
  • KNIME Verified Components - knime.com

Used extensions & nodes

Created with KNIME Analytics Platform version 4.4.2
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

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    KNIME Plotly Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

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