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H2O.ai AutoML (wrapped with Python) in KNIME for classification problems

H2oAutomlKnimeXgboost
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Jan 23, 2020 8:19 PM
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H2O.ai AutoML in KNIME for classification problems a powerful auto-machine-learning framework https://hub.knime.com/mlauber71/spaces/Public/latest/automl/ kn_automl_h2o_classification_python H2O.ai AutoML in KNIME for classification problems https://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923 It features various models like Random Forest or XGBoost along with Deep Learning. It has warppers for R and Python but also could be used from KNIME. The results will be written to a folder and the models will be stored in MOJO format to be used in KNIME (as well as on a Big Data cluster via Sparkling Water). One major parameter to set is the running time the model has to test various models and do some hyper parameter optimization as well. The best model of each round is stored and some graphics are produced to see the results. Results are interpreted thru various statistics and model characteristics are stored in and Excel und TXT file as well as in PNG graphics you can easily re-use in presentations and to give your winning models a visual inspection. Also, you could use the Metanode “Model Quality Classification - Graphics” to evaluate other binary classification models To run this workflow you have to install Python and H2O.ai as well as R and several packages. Please refer to the green box on the right. The results may be used also on Big Data clusters with the help of H2O.ai Sparkling Water (https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_h2o_sparkling_water)

External resources

  • H2O.ai AutoML in KNIME for classification problems
  • Combine Big Data, Spark and H2O.ai Sparkling Water
  • A Deep dive into H2O’s AutoML
  • Profile mlauber71
  • KNIME Python Integration Installation Guide
  • KNIME, Python and Anaconda - the short story
  • 11 Important Model Evaluation Metrics for Machine Learning Everyone should know
  • Downloading & Installing H2O
  • Kaggle - House Prices: Advanced Regression Techniques
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.2
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    KNIME CoreTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

    knime
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    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

    knime
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    KNIME Extension for Big Data File FormatsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime
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    KNIME H2O Machine Learning Integration - MOJO ExtensionTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime
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    KNIME Interactive R Statistics IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

    knime
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    KNIME JavaScript ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

    knime
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    KNIME Machine Learning Interpretability ExtensionTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime
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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime
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    KNIME Python Integration

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

    knime
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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

    knime
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    KNIME SVG SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime

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