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.
EXAMPLES Server: 04_Analytics/13_Meta_Learning/04_Cross-Platform_Ensemble_Model04_Analytics/13_Meta_Learning/04_Cross-Platform_Ensemble_Model*
Download a zip-archive
- A Cross-Platform Ensemble Model. R meets Python and, of course, KNIME. Embrace Freedom in the Data Science Lab.
* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually