ML Anthology

Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

Usama M. Fayyad, Keki B. Irani
IJCAI 1993 pp. 1022-1029
/ijcai/1993/fayyad1993ijcai-multi/

Abstract

Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.

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Text

Fayyad and Irani. "Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning." International Joint Conference on Artificial Intelligence, 1993.

Markdown

[Fayyad and Irani. "Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning." International Joint Conference on Artificial Intelligence, 1993.](https://mlanthology.org/ijcai/1993/fayyad1993ijcai-multi/)

BibTeX

@inproceedings{fayyad1993ijcai-multi,
  title     = {{Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning}},
  author    = {Fayyad, Usama M. and Irani, Keki B.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1993},
  pages     = {1022-1029},
  url       = {https://mlanthology.org/ijcai/1993/fayyad1993ijcai-multi/}
}