WIT Press


Precision And Comprehensibility In The Integration Of Regression Rules

Price

Free (open access)

Paper DOI

10.2495/DATA030541

Volume

29

Pages

10

Published

2003

Size

516 kb

Author(s)

J. B. Pugliesi & S. O. Rezende

Abstract

Precision and comprehensibility in the integration of regression rules J. B. Pugliesi & S. 0. Rezende Institute of Mathematics and Computer Sciences-ICMC, University of Siio Paulo-US8 Siio Carlos, Brazil Abstract Data Mining is the process of data analysis and application of algorithms that are able to find a particular pattern relationship from a large amount of data. Regression is an important problem in data analysis and appears in many real world applications. Therefore, there is an increasing interest in the use of the Data Mining to extract patterns from regression problems. The main objective of this paper is to support the users of Data Mining process in the evaluation of integrated knowledge expressed in the form of regression rules. To explore the knowledge evaluation, experiments are executed with Cubist, RT and M5 algorithms. The 10-fold crossvalidation is used to find the mean error. All regression rules are transformed to a standard syntax and put together in a unique set of rules

Keywords