Application of Machine Learning to Identify State Drivers

  • Thorsten WuestEmail author
Part of the Springer Theses book series (Springer Theses)


In this section, the application of ML is investigated in further detail. First ML is briefly introduced in more detail with respect to the manufacturing domain. Based on this brief general elaboration, SVM algorithms are selected as a suitable ML technique to match the detailed requirements of the stated research problem. In the final subsection, the application of SVM is discussed towards its objective of identification of state drivers in manufacturing programmes. Within this last subsection, the application and evaluation approach of the SVM application are presented and the derived hypotheses are detailed based on the decision to use the SVM algorithm to conclude the section.


Support Vector Machine Classification Performance Research Problem State Driver Support Vector Machine Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of ICT Applications for ProductionBIBA—Bremer Institut für Produktion und Logistik GmbHBremenGermany
  2. 2.Department of Production EngineeringUniversity of BremenBremenGermany

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