- author = "Karla Taboada and Eloy Gonzales and Kaoru Shimada and Shingo Mabu and Kotaro Hirasawa and Jinglu Hu",
- title = "Mining Association Rules from Databases with Continuous Attributes using Genetic Network Programming",
- booktitle = "2007 IEEE Congress on Evolutionary Computation",
- year = "2007",
- editor = "Dipti Srinivasan and Lipo Wang",
- pages = "1311--1317",
- address = "Singapore",
- month = "25-28 " # sep,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- ISBN = "1-4244-1340-0",
- file = "1162.pdf",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/CEC.2007.4424622",
- abstract = "Most association rule mining algorithms make use of discretisation algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute value into a finite number of intervals and assigning each interval to a discrete numerical value. However, by means of methods of discretisation, it is difficult to get highest attribute interdependency and at the same time to get lowest number of intervals. In this paper we present an association rule mining algorithm that is suited for continuous valued attributes commonly found in scientific and statistical databases. We propose a method using a new graph-based evolutionary algorithm named {"}Genetic Network Programming (GNP){"} that can deal with continues values directly, that is, without using any discretisation method as a preprocessing step. GNP represents its individuals using graph structures and evolve them in order to find a solution; this feature contributes to creating quite compact programs and implicitly memorising past action sequences. In the proposed method using GNP, the significance of the extracted association rule is measured by the use of the chi-squared test and only important association rules are stored in a pool all together through generations. Results of experiments conducted on a real life database suggest that the proposed method provides an effective technique for handling continuous attributes.",
-
notes = "CEC 2007 - A joint meeting of the IEEE, the EPS, and
the IET.
IEEE Catalog Number: 07TH8963C",
