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Analytics - Model Selection to Predict Flight Departure Delays

Data scienceMachine learningModel selectionData preparationETL
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lukass profile image
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Sep 26, 2016 1:32 PM
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This workflow trains a number of data analytics models and automatically selects the best model to predict departure delays from a selected airport. Data is the airline dataset downloadable from: http://stat-computing.org/dataexpo/2009/the-data.html. Departure delay is a delay > 15min. Default selected airport is ORD. This workflow implements data reading, ETL, outlier detection, dimensionality reduction, feature generation, feature selection, advanced data mining models, model selection and comparison. Data available in knime://knime.workflow/data/

External resources

  • KNIME Analytics: a Review
  • Advanced ETL Functionalities and Machine Learning Pre-Processing
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Created with KNIME Analytics Platform version 4.5.0
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    KNIME AG, Zurich, Switzerland

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    KNIME AG, Zurich, Switzerland

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    KNIME Statistics NodesTrusted extension

    KNIME AG, Zurich, Switzerland

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