Comprehensive PMML preprocessing in KNIME

Authors:
Dominik Morent;Kostantinos Stathatos;Wen-Ching Lin;Michael R. Berthold
Affiliations:
KNIME.com GmbH, Zürich, Switzerland;Zementis Inc, San Diego, CA, USA;Zementis Inc, San Diego, CA, USA;University of Konstanz, Konstanz, Germany
Venue:
Proceedings of the 2011 workshop on Predictive markup language modeling
Year:
2011

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Abstract

This paper describes PMML extensions for the modular open source data analytics platform KNIME adding pre-processing support and the ability to edit existing PMML code. It is also shown how the PMML model representation in KNIME can be used within meta learning schemes such as boosting and bagging.