Breast cancer data analysis using support vector machines and particle swarm optimization

@article{Arafi2014BreastCD,
  title={Breast cancer data analysis using support vector machines and particle swarm optimization},
  author={Ayoub Arafi and Rkia Fajr and Abdelaziz Bouroumi},
  journal={2014 Second World Conference on Complex Systems (WCCS)},
  year={2014},
  pages={1-6}
}
We propose a machine learning method for breast cancer data analysis and classification, based on support vector machines (SVM) and particle swarm optimization (PSO). This method uses SVM as a model for supervised learning with the goal of minimizing generalization errors, and PSO as an optimization technique for automatic determination of the best values of two algorithmic parameters of SVM. Its performance in solving classification and recognition problems is experimentally tested for a real… CONTINUE READING

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References

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Showing 1-9 of 9 references

Blue , " A support vector machine approach to decision trees

K. P. Bennett, J. a.
IEEE World Congr . Comput . Intel I . ( Cat . No . • 2013

Lichman, UCI Machine Learning Repository, University of California

M. K. Bache
School of Information and Computer Science, Irvine, • 2013
View 2 Excerpts

Fuzzy support vector machines

IEEE Trans. Neural Networks • 2002
View 2 Excerpts

and P

D. M. Parkin, F. Bray, J. Ferlay
Pisani, "Global cancer statistics, • 2002

Particle swarm optimization,

J. Kennedy, R. c. Eberhart
Proc. IEEE in'l conf. on neural networks, • 1995
View 2 Excerpts

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