Complexity Measures of Supervised Classification Problems

@article{Ho2002ComplexityMO,
  title={Complexity Measures of Supervised Classification Problems},
  author={Tin Kam Ho and Mitra Basu},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
  year={2002},
  volume={24},
  pages={289-300}
}
ÐWe studied a number of measures that characterize the difficulty of a classification problem, focusing on the geometrical complexity of the class boundary. We compared a set of real-world problems to random labelings of points and found that real problems contain structures in this measurement space that are significantly different from the random sets. Distributions of problems in this space show that there exist at least two independent factors affecting a problem's difficulty. We suggest… CONTINUE READING
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References

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Showing 1-10 of 28 references

ªMultiple Classifier Combination: Lessons and Next Steps,º Hybrid Methods in Pattern Recognition

  • T K Ho
  • World Scientific
  • 2002
1 Excerpt

Pattern Recognition: A Review IEEE Trans. Pattern Analysis and Machine Intelligence

  • A K Jain, R P W Duin, J Mao
  • Pattern Recognition: A Review IEEE Trans. Pattern…
  • 2000
1 Excerpt

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