Development and Evaluation of Cost-Sensitive Universum-SVM

@article{Dhar2015DevelopmentAE,
  title={Development and Evaluation of Cost-Sensitive Universum-SVM},
  author={Sauptik Dhar and Vladimir Cherkassky},
  journal={IEEE Transactions on Cybernetics},
  year={2015},
  volume={45},
  pages={806-818}
}
Many machine learning applications involve analysis of high-dimensional data, where the number of input features is larger than/comparable to the number of data samples. Standard classification methods may not be sufficient for such data, and this provides motivation for nonstandard learning settings. One such new learning methodology is called learning through contradiction or Universum-support vector machine (U-SVM). Recent studies have shown U-SVM to be quite effective for sparse high… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

Cost-sensitive SVDD models based on a sample selection approach

Applied Intelligence • 2018
View 16 Excerpts
Highly Influenced

Investor sentiment identification based on the universum SVM

Neural Computing and Applications • 2016
View 5 Excerpts
Highly Influenced

Universum learning for SVM regression

2017 International Joint Conference on Neural Networks (IJCNN) • 2017

References

Publications referenced by this paper.
Showing 1-10 of 21 references

Seizure prediction with spectral power of time/space-differential EEG signals using cost-sensitive support vector machine

2010 IEEE International Conference on Acoustics, Speech and Signal Processing • 2010
View 6 Excerpts
Highly Influenced

The Foundations of Cost-Sensitive Learning

IJCAI • 2001
View 7 Excerpts
Highly Influenced

Estimation of Dependencies Based on Empirical Data: Empirical Inference Science: Afterword

V. N. Vapnik
2006
View 7 Excerpts
Highly Influenced

Learning from Data: Concepts, Theory, and Methods

Technometrics • 2001
View 10 Excerpts
Highly Influenced

Cost-Sensitive Universum-SVM

2012 11th International Conference on Machine Learning and Applications • 2012
View 2 Excerpts

UBoost: Boosting with the Universum

IEEE Trans. Pattern Anal. Mach. Intell. • 2012
View 3 Excerpts

Similar Papers

Loading similar papers…