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Synthetic Data Generator (Classification)

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This component generates example data for classification tasks based on the make_classification() function in the Python scikit-learn library. The predictor features are randomly drawn from the standard normal distribution. If desired, some of the features can be redundant or duplicated. The samples are assigned into one or more clusters within each class. Furthermore, it is possible to regulate the class separation within the feature space. For more information see the sklearn documentation: scikit-learn.org/stable/modules/generated/sklearn.datasets.make_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
    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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