GEPCLASS: A Classification Rule Discovery Tool Using Gene Expression Programming

Abstract

Abstract. This work describes the use of a recently proposed technique -gene expression programming -for knowledge discovery in the data mining task of data classification. We propose a new method for rule encoding and genetic operators that preserve rule integrity, and implemented a system, named GEPCLASS. Due to its encoding scheme, the system allows the automatic discovery of flexible rules, better fitted to data. The performance of GEPCLASS was compared with two genetic programming systems and with C4.5, over four data sets in a five-fold cross-validation procedure. The predictive accuracy for the methods compared were similar, but the computational effort needed by GEPCLASS was significantly smaller than the other. GEPCLASS was able to find simple and accurate rules as it can handle continuous and categorical attributes.

Evolving Classifier Ensemble With Gene Expression Programming

“…Weinert [14] used different individual encoding to tackle with the closure requirement of logical or rational function of their GEPCLASS system. GEPCLASS used logical and rational functions instead of arithmetical functions to solve classification problems.…”

Data mining with a parallel rule induction system based on gene expression programming

“…After the basic GEP, some improvements were proposed in two specific domains: EGIPSYS (Lopes and Weinert, 2004), for symbolic regression; and GEPCLASS (Weinert and Lopes, 2006), for data classification. In GEPCLASS, an individual is composed by a single chromosome which, in turn, is composed by a number of genes.…”

A Comparative Study of Machine Learning and Evolutionary Computation Approaches for Protein Secondary Structure Classification

“…The instances in this relational attribute consist of single nominal data instances using the natural encoding of the protein sequence, i.e., the string of letters representingthe amino acid sequence(forexample,"GLY,TRP,LEU,...,LEU"). Finally, Gene Expression Programming (GEP) was used for generating classification rules by means of the software GEPCLASS (Weinert & Lopes, 2006). The input file to GEP is similar to the ARFF file that was used before, but without header information, just with the real-valued data instances as detailed in the section 6.1.…”

“…Selected individuals naturally go through modifications by means of genetic operators leading to a new generation of individuals. The whole process is repeated until a stopping criterion is met (Weinert & Lopes, 2006). The structural organization of GEP genes are based on Open Reading Frames (ORF), a biological terminology.…”

“…Besides the genetic operations like replication, mutation and recombination, GEP includes operations based on transpositions and insertion of elements. In this work, we used the GEPCLASS system 3 that was specially developed for data classification with some modifications regarding the original GEP algorithm (Weinert & Lopes, 2006).…”