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  • 01_Guided_Labeling_for_Document_Classification
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Guided Labeling for Document Classification

Active learning Human-in-the-loop Guided analytics Document classification Sentiment analysis
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This workflow defines a fully automated web based application that will label your data using active learning. The workflow was designed for business analysts to easily go through documents to be labeled in any number of classes. In each iteration the user labels more documents and the model is trained using the already labeled instances. With every new iteration, the model proposes the most uncertain documents using the entropy scorer node. Once the user is happy with the performance achieved with the available labels, they can exit the loop and export the model to label the remaining instances.

External resources

  • Burr Settles, Active Learning Literature Survey, 2010 - Chapter 3.1 Uncertainty Sampling

Used extensions & nodes

Created with KNIME Analytics Platform version 4.0.1
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    KNIME Active Learning Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

    knime
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.1

    knime
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    KNIME Data Generation Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

    knime
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    KNIME Expressions Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.1

    knime
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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.1

    knime
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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

    knime
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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.1

    knime
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    KNIME Textprocessing Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.2

    knime
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    KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.0, 4.0.1

    knime
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