Data Abstractions for Numerical Attributes in Data Mining

@inproceedings{Narita2002DataAF,
  title={Data Abstractions for Numerical Attributes in Data Mining},
  author={Masaaki Narita and Makoto Haraguchi and Yoshiaki Okubo},
  booktitle={IDEAL},
  year={2002}
}
In this paper, we investigate data abstractions for mining association rules with numerical conditions and boolean consequents as a target class. The act of our abstraction corresponds to joining some consecutive primitive intervals of a numerical attribute. If the interclass variance for two adjacent intervals is less than a given admissible upperbound… CONTINUE READING