Machine training and parameter settings with social emotional optimization algorithm for support vector machine

@article{Zhang2015MachineTA,
  title={Machine training and parameter settings with social emotional optimization algorithm for support vector machine},
  author={Yunqiang Zhang and Peilin Zhang},
  journal={Pattern Recognition Letters},
  year={2015},
  volume={54},
  pages={36-42}
}
Abstract Machine training along with the parameter settings significantly influences the performance of support vector machine (SVM). In this paper, the social emotional optimization algorithm (SEOA) characterized by excellent global optimization ability is employed for machine training and parameter settings for SVM. Instead of the quadratic programming problem, machine training for SVM is modeled as a multi-parameter optimization problem which is solved by SEOA. Besides, SEOA is also employed… CONTINUE READING

Topics from this paper.

Similar Papers