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Kullback–Leibler divergence

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Versionv1.0Latest, created on 
Mar 7, 2024 2:18 PM
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This component computes the Kullback-Leibler divergence to output a measure of dissimilarity between two distribution of the same variable, which come from two different datasets. It could be very useful to identify shift inside data which can potentially lead to a model drift, downgrading the predictive power. Column names and types must be identical between the two tables. Continous predictors are binned into classes to make computation of the metric easier. A value close to 0 means that the two variables have the same distribution. As the value increases, the dissimilarity is higher. Columns must have the same name and the same data type.

Component details

Input ports
  1. Type: Table
    Table 1
    Input table 1
  2. Type: Table
    Table 2
    Input table 2
Output ports
  1. Type: Table
    Kullback-Leibler measure
    Kullback-Leibler measure for each input column

Used extensions & nodes

Created with KNIME Analytics Platform version 4.6.0
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    knime

This component does not have nodes, extensions, nested components and related workflows

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