Feature Set Reduction for Document Classification Problems

@inproceedings{Fuka2001FeatureSR,
  title={Feature Set Reduction for Document Classification Problems},
  author={arel Fuka and Rudolf Hanka},
  year={2001}
}
With a growing amount of electronic documents available, there is a need to classify documents automatically. In growing text classification applications, important-term selection is a critical task for the classifier performance. Although many different techniques and heuristics have been developed, this paper shows that many of them are just a sub-set of more advanced methods originating in the field of pattern recognition. The paper puts these techniques into the pattern recognition context… CONTINUE READING