Hybrid GA-SVM for Efficient Feature Selection in E-mail Classification

@inproceedings{Temitayo2012HybridGF,
  title={Hybrid GA-SVM for Efficient Feature Selection in E-mail Classification},
  author={Fagbola Temitayo and Olabiyisi Stephen and Adigun Abimbola},
  year={2012}
}
Feature selection is a problem of global combinator i l ptimization in machine learning in which subse ts of relevant features are selected to realize robust le arning models. The inclusion of irrelevant and redu ndant features in the dataset can result in poor predicti ons and high computational overhead. Thus, selectin g relevant feature subsets can help reduce the comput ational cost of feature measurement, speed up learn ing process and improve model interpretability. SVM cla ssifier has… CONTINUE READING
Highly Cited
This paper has 32 citations. REVIEW CITATIONS