SLIQ: A Fast Scalable Classifier for Data Mining

@inproceedings{Mehta1996SLIQAF,
  title={SLIQ: A Fast Scalable Classifier for Data Mining},
  author={Manish Mehta and Rakesh Agrawal and Jorma Rissanen},
  booktitle={EDBT},
  year={1996}
}
Classi cation is an important problem in the emerging eld of data mining. Although classi cation has been studied extensively in the past, most of the classi cation algorithms are designed only for memory-resident data, thus limiting their suitability for data mining large data sets. This paper discusses issues in building a scalable classier and presents the design of SLIQ, a new classi er. SLIQ is a decision tree classi er that can handle both numeric and categorical attributes. It uses a… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 13 references

Ctr

  • NASA Ames Res
  • Intro. to IND Version 2.1, GA23-2475-02 edition,
  • 1992
Highly Influential
15 Excerpts

Quinlan

  • J. Ros
  • C4.5: Programs for Machine Learning. Morgan…
  • 1993
Highly Influential
4 Excerpts

et

  • L. Breima
  • al. Classi cation and Regression Trees. Wadsworth…
  • 1984
Highly Influential
9 Excerpts

et

  • R. Agrawa
  • al. An interval classi er for database mining…
  • 1992