Breast cancer detection with logistic regression improved by features constructed by Kaizen programming in a hybrid approach

@article{Melo2016BreastCD,
  title={Breast cancer detection with logistic regression improved by features constructed by Kaizen programming in a hybrid approach},
  author={Vinicius Veloso de Melo},
  journal={2016 IEEE Congress on Evolutionary Computation (CEC)},
  year={2016},
  pages={16-23}
}
Breast cancer is known as the second largest cause of cancer deaths among women, but thankfully it can be cured if diagnosed early. There have been many investigations on methods to improve the accuracy of the diagnostic, and Machine Learning (ML) and Evolutionary Computation (EC) tools are among the most successfully employed modern methods. On the other hand, Logistic Regression (LR), a traditional and popular statistical method for classification, is not commonly used by computer scientists… CONTINUE READING

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