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Active Learning with Modular Score

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This workflow shows an example of Active Learning. We read a simple dataset of images separated in two classes and calculate some features on them. Now the Active Learning Loop determines the best sample which could be manuallay labeled by a user and benefits most to the separation of the calsses. The decision of the best sample is based on a specific score. Here we use a modular score calculation approach in order to find the best sample.

External resources

  • KNIME Active Learning

Used extensions & nodes

Created with KNIME Analytics Platform version 3.7.1
  • KNIME Active Learning Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 3.7.0

  • KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 3.7.1

  • KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.7.0

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License (CC-BY-4.0)
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