Performance analysis of support vector machines classifiers in breast cancer mammography recognition

@article{Azar2012PerformanceAO,
  title={Performance analysis of support vector machines classifiers in breast cancer mammography recognition},
  author={Ahmad Taher Azar and Shaimaa Ahmed El-Said},
  journal={Neural Computing and Applications},
  year={2012},
  volume={24},
  pages={1163-1177}
}
Support vector machine (SVM) is a supervised machine learning approach that was recognized as a statistical learning apotheosis for the small-sample database. SVM has shown its excellent learning and generalization ability and has been extensively employed in many areas. This paper presents a performance analysis of six types of SVMs for the diagnosis of the classical Wisconsin breast cancer problem from a statistical point of view. The classification performance of standard SVM (St-SVM) is… CONTINUE READING
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