Supervised term weighting centroid-based classifiers for text categorization

@article{Nguyen2012SupervisedTW,
  title={Supervised term weighting centroid-based classifiers for text categorization},
  author={Tam T. Nguyen and Kuiyu Chang and Siu Cheung Hui},
  journal={Knowledge and Information Systems},
  year={2012},
  volume={35},
  pages={61-85}
}
In this paper, we study the theoretical properties of the class feature centroid (CFC) classifier by considering the rate of change of each prototype vector with respect to individual dimensions (terms). We show that CFC is inherently biased toward the larger (dominant majority) classes, which invariably leads to poor performance on class-imbalanced data. CFC also aggressively prune terms that appear across all classes, discarding some non-exclusive but useful terms. To overcome these CFC… CONTINUE READING

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