Enhancing the Accuracy 0 F Svm Classifiers with Kernel and Parameter Training

@inproceedings{UDHAYAKUMARAPANDIAN2015EnhancingTA,
  title={Enhancing the Accuracy 0 F Svm Classifiers with Kernel and Parameter Training},
  author={D. UDHAYAKUMARAPANDIAN and Rm. Chandrasekaran and Ammasai Kumaravel},
  year={2015}
}
Data mining methods based on support vector machine are attractive to address the curse of dimensionality. The Kernel mapping contributes a unifying frame work for most of the commonly employed models to get the linear planes in the higher dimensional space. In this paper, we prove this approach enhances the accuracy of diabetes data set. We further refine the results with parameter tuning for the selected kernels. The natural question that arises in case of many such different mappings to… CONTINUE READING
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