GSVM: An SVM for handling imbalanced accuracy between classes inbi-classification problems

  title={GSVM: An SVM for handling imbalanced accuracy between classes inbi-classification problems},
  author={Luis Gonz{\'a}lez Abril and Haydemar N{\'u}{\~n}ez and Cecilio Angulo and Francisco Velasco Morente},
  journal={Appl. Soft Comput.},
A new Support Vector Machine, SVM, is introduced, called GSVM, which is specially designed for bi-classication problems where balanced accuracy between classes is the objective. Starting from a standard SVM, the GSVM is obtained from a low-cost post-processing strategy by modifying the initial bias. Thus, the bias for GSVM is calculated by moving the original bias in the SVM to improve the geometric mean between the true positive rate and the true negative rate. The proposed solution neither… CONTINUE READING
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A study on output normalization in multiclass svms

  • L. Gonzalez-Abril, F. Velasco, C. Angulo, J. A. Ortega
  • Pattern Recognition Letters
  • 2013
1 Excerpt

On the effectiveness of preprocessing methods when dealing with different levels of class imbalance

  • V. Garćıa, J. Sánchez, R. Mollineda
  • Knowledge-Based Systems
  • 2012
1 Excerpt

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