Hepatitis-C Classification using Data Mining Techniques

@inproceedings{Yasin2011HepatitisCCU,
  title={Hepatitis-C Classification using Data Mining Techniques},
  author={Huda Yasin and Tahseen Ahmed Jilani},
  year={2011}
}
In this paper, we scrutinize factors that dole out significantly to augmenting the risk of hepatitis-C virus. The dataset has been taken from the machine learning warehouse of University of California. It contains nineteen features along with a class feature having binary classification. There is a total of 15 binary attributes together with a class attribute and 5 continuous attributes. The dataset contains 155 records. In order to prevail over the missing 
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