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Pattern Recognition Engineering

Faisal Shafait, Matthias Reif, Christian Kofler, Thomas Breuel

RapidMiner Community Meeting and Conference RapidMiner Community Meeting and Conference (RCOMM-10), September 13-16, Dortmund, Germany , Online , 2010
This paper outlines some key software components developed in the Pattern Recognition Engineering (PaREn) project. The goal of the PaREn project was to create the methods and tools necessary allowing non-experts to use, train, test, and deploy pattern recognition and machine learning modules in real-world software systems. A major effort in the PaREn project was therefore automating parameter optimization, model selection, machine learning system construction, and supporting rapid testing, validation, and on-line adaptivity. To deliver our technologies as open source, we chose RapidMiner as the software platform. Therefore, major software components developed in PaREn are provided as RapidMiner extensions. The expected benefits are a far wider usage of pattern recognition and machine learning methods, leading to both better quality of the decisions and behaviors of software systems, as well as lower development costs.

Show BibTex:

@inproceedings {
       abstract = {This paper outlines some key software components
developed in the Pattern Recognition Engineering (PaREn)
project. The goal of the PaREn project was to create the
methods and tools necessary allowing non-experts to use, train,
test, and deploy pattern recognition and machine learning
modules in real-world software systems. A major effort in the
PaREn project was therefore automating parameter optimization, model selection, machine learning system construction,
and supporting rapid testing, validation, and on-line adaptivity.
To deliver our technologies as open source, we chose RapidMiner as the software platform. Therefore, major software
components developed in PaREn are provided as RapidMiner
extensions. The expected benefits are a far wider usage of
pattern recognition and machine learning methods, leading to
both better quality of the decisions and behaviors of software
systems, as well as lower development costs.},
       number = {}, 
       month = {9}, 
       year = {2010}, 
       title = {Pattern Recognition Engineering}, 
       journal = {}, 
       volume = {}, 
       pages = {}, 
       publisher = {Online}, 
       author = {Faisal Shafait, Matthias Reif, Christian Kofler, Thomas Breuel}, 
       keywords = {},
       url = {http://www.dfki.de/web/forschung/publikationen/renameFileForDownload?filename=Shafait-PaREn-RCOMM10.pdf&file_id=uploads_780}
}