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Constructing X-of-N attributes with a genetic algorithm

Larsen, O., Freitas, Alex A., Nievola, Julio C. (2002) Constructing X-of-N attributes with a genetic algorithm. In: Lofti, A. and Garibaldi, J. and John, R., eds. Proc. 4th Int. Conf. on Recent Advances in Soft Computing (RASC-2002). . pp. 326-331. Nottingham Trent University (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:13696)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.

Abstract

The predictive accuracy obtained by a classification

algorithm is strongly dependent on the quality of the

attributes of the data being mined. When the attributes are

little relevant for predicting the class of a record, the

predictive accuracy will tend to be low. To combat this

problem, a natural approach consists of constructing new

attributes out of the original attributes. Many attribute

construction algorithms work by simply constructing

conjunctions and/or disjunctions of attribute-value pairs.

This kind of representation has a limited expressiveness

power to represent attribute interactions. A more

expressive representation is X-of-N [Zheng 1995]. An Xof-

N condition consists of a set of N attribute-value pairs.

The value of an X-of-N condition for a given example

(record) is the number of attribute-value pairs of the

example that match with the N attribute-value pairs of the

condition. For instance, consider the following X-of-N

condition: X-of-{“Sex = male”, “Age < 21”, “Salary =

high”}. Suppose that a given example has the following

attribute-value pairs: {“Sex = male”, “Age = 51”, “Salary

= high”}. This example has 2 out of the 3 attribute-value

pairs of the X-of-N condition, so that the value of the Xof-

N condition for this example is 2.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: genetic algorithms, constructive induction, data mining
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 17:59 UTC
Last Modified: 16 Nov 2021 09:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/13696 (The current URI for this page, for reference purposes)

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