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Mr Peter Reutemann

Senior Research Programmer (Computer Science)

Qualifications: MSc CS Freiburg

Contact Details

Email: fracpete@waikato.ac.nz
Room: G.2.19
Phone: +64 7 858 5174
Extension: 5174
Fax: +64 7 838 4155
Website: http://www.cms.waikato.ac.nz/~fracpete/

About Peter

Open-source advocate, specialized in workflow engines, machine learning and data mining. Lead developer of the ADAMS workflow engine.

Research Interests

Some of the research projects Peter has been involved in are:

Recent Publications

  • Read, J., Reutemann, P., Pfahringer, B., & Holmes, G. (2016). MEKA: A multi-label/multi-target extension to WEKA. Journal of Machine Learning Research, 17(21), 1-5. Open Access version: https://hdl.handle.net/10289/10136

  • Reutemann, P., & Holmes, G. (2015). Big data with ADAMS. In 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications Vol. 41 (pp. 5-8). Sydney, Australia: JMLR Workshop and Conference Proceedings. Retrieved from http://jmlr.org/proceedings/papers/v41/reutemann15.html

  • Hill, M. G., Connolly, P. G., Reutemann, P., & Fletcher, D. (2014). The use of data mining to assist crop protection decisions on kiwifruit in New Zealand. Computers and Electronics in Agriculture, 108, 250-257. doi:10.1016/j.compag.2014.08.011

  • Holmes, G., Fletcher, D., & Reutemann, P. (2012). An application of data mining to fruit and vegetable sample identification using Gas Chromatography-Mass Spectrometry. In R. Seppelt, A. A. Voinov, S. Lange, & D. Bankamp (Eds.), Proc Sixth Biennial Meeting of the International Environmental Modelling and Software Society (iEMSs), Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty (pp. 1577-1584). Conference held at Leipzig, Germany: iEMSs. Retrieved from http://www.iemss.org/sites/iemss2012/proceedings.html Open Access version: https://hdl.handle.net/10289/8409

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