Review and performance comparison of SVM- and ELM-based classifiers

@article{Chorowski2014ReviewAP,
  title={Review and performance comparison of SVM- and ELM-based classifiers},
  author={Jan Chorowski and Jian Wang and Jacek M. Zurada},
  journal={Neurocomputing},
  year={2014},
  volume={128},
  pages={507-516}
}
This paper presents how commonly used machine learning classifiers can be analyzed using a common framework of convex optimization. Four classifier models, the Support Vector Machine (SVM), the Least-Squares SVM (LSSVM), the Extreme Learning Machine (ELM), and the Margin Loss ELM (MLELM) are discussed to demonstrate how specific parametrizations of a general problem statement affect the classifier design and performance, and how ideas from the four different classifiers can be mixed and used… CONTINUE READING
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