Feature selection using support vector machines

  title={Feature selection using support vector machines},
  author={Janez. Brank and Marko Grobelnik and Natasa Milic-Frayling and Dunja. Mladenic},
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
Highly Influential
This paper has highly influenced a number of papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 376 citations. REVIEW CITATIONS

4 Figures & Tables



Citations per Year

376 Citations

Semantic Scholar estimates that this publication has 376 citations based on the available data.

See our FAQ for additional information.