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Mixing Deep Learning with XGBoost

Deep Learning Machine Learning XGBoost Data Mining Classification
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This workflow shows how to train an XGBoost based image classifier that uses a pretrained convolutional neural network to extract features from images. It also contains shows how the extracted features can be used to visualize an image dataset with t-SNE.

External resources

  • Link to pretrained network
  • Link to data

Used extensions & nodes

Created with KNIME Analytics Platform version 4.0.2
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.0.1, 4.0.2

    knime
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    KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.2

    knime
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    KNIME Deep Learning - TensorFlow Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

    knime
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    KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.8.0

    bioml-konstanz
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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.1

    knime
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    KNIME Statistics Nodes (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

    knime
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    KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.1

    knime
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