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  • Synthetic Data Generator (Multilabel Classification)
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Synthetic Data Generator (Multilabel Classification)

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This component generates example data for a multilabel classification task based on the make_multilabel_classification() function in the Python scikit-learn library. It generates class columns with 0s/1s that indicate the absence/presence of the respective label. The average number of labels assigned to each row can be regulated. For more information see the sklearn documentation: scikit-learn.org/stable/modules/generated/sklearn.datasets.make_multilabel_classification.html Note: This component requires a Python environment. In this blog post we explain how to setup the KNIME Python extension: knime.com/blog/setting-up-the-knime-python-extension-revisited-for-python-30-and-20

Component details

Output ports
  1. Type: Table
    Port 1
    Multi-class Classification Data

Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.2
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    KNIME profile image
    knime
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    KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    KNIME profile image
    knime
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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    KNIME profile image
    knime
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By using or downloading the component, you agree to our terms and conditions.

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