Feature selection using support vector machines

@inproceedings{Brank2002FeatureSU,
  title={Feature selection using support vector machines},
  author={Janez. Brank and Marko Grobelnik and Natasa Milic-Frayling and Dunja. Mladenic},
  year={2002}
}
Text categorization is the task of classifying natural language documents into a set of predefined categories. Documents are typically represented by sparse vectors under the vector space model, where each word in the vocabulary is mapped to one coordinate axis and its occurrence in the document gives rise to one nonzero component in the vector representing that document. When training classifiers on large collections of documents, both the time and memory requirements connected with processing… CONTINUE READING
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