Binary classification of cancer microarray gene expression data using extreme learning machines

@article{Kumar2014BinaryCO,
  title={Binary classification of cancer microarray gene expression data using extreme learning machines},
  author={C. Kumar and S. Ramakrishnan},
  journal={2014 IEEE International Conference on Computational Intelligence and Computing Research},
  year={2014},
  pages={1-4}
}
  • C. Kumar, S. Ramakrishnan
  • Published 2014
  • Computer Science
  • 2014 IEEE International Conference on Computational Intelligence and Computing Research
This paper presents the usage of Extreme Learning Machines for cancer microarray gene expression data. Extreme Learning Machines overcomes the problems of overfitting, local minima and improper training rate that are most common in traditional algorithms. We have evaluated the binary classification performance of Extreme Learning Machines on five bench marked datasets of cancer microarray gene expression data namely ALL/AML, CNS, Lung Cancer, Ovarian Cancer and Prostate Cancer. Feature… Expand
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