Extracting Knowledge from Databases and ANNs with Genetic Programming: Iris Flower Classification Problem

Extracting Knowledge from Databases and ANNs with Genetic Programming: Iris Flower Classification Problem

Daniel Rivero (University of A Coruna, Spain), Juan R. Rabunal (University of A Coruña, Spain), Julián Dorado (University of A Coruña, Spain), Alejandro Pazos (University of A Coruña, Spain) and Nieves Pedreira (University of A Coruña, Spain)
Copyright: © 2004 |Pages: 17
DOI: 10.4018/978-1-59140-194-0.ch009
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Abstract

In this chapter, we present an application of Genetic Programming (GP) in the field of data mining and extraction of Artificial Neural Networks (ANN) rules. To do this, we will use its syntactic properties to obtain high level expressions that represent knowledge. These expressions will have different types as there is the need at each moment: we will obtain different expressions like IF-THEN-ELSE rules, mathematical relations between variables or boolean expressions. In this chapter, we will not only apply GP to solve the problem, but we will try different modifications and different ways to apply it to solve the problem. We will show how making a data pre-processing we can obtain better results than using the original values. That is, by adding a little knowledge from the problem we can improve the performance of GP.

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