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Will they blend? An Ensemble model from R, Python, and KNIME models

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The challenge is to blend together models from different analytics platforms - i.e. Python , R, and KNIME - to create an ensemble model. Data is the “airline data set” (http://stat-computing.org/dataexpo/2009/the-data.html) enriched with additional external data , such as cities, daily weather (https://www.ncdc.noaa.gov/cdo-web/datasets/), US holidays, geo-coordinates, airplane maintenance. DepDealys is used as the target variable. R SVM, Python Logisitc Regression, and KNIME Decision Tree. Will they blend in a single ensemble model? ... and yes! They blend.

External resources

  • A Cross-Platform Ensemble Model. R meets Python and, of course, KNIME. Embrace Freedom in the Data Science Lab.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.2
  • KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

  • KNIME Ensemble Learning Wrappers Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Interactive R Statistics Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

  • KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

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License (CC-BY-4.0)
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